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"the entanglement between users' practices to disguise and amplify racist humour and abuse, and the contribution of platforms' features and algorithms in the circulation of overt and covert hate speech." }, { "citation": [], "text": "On the one hand, it evokes platforms as amplifiers and manufacturers of racist discourse by means of their affordances and users' appropriation of them (e.g. like button vs \"dislike\" button, sharing and liking practices that influence platforms' algorithms). 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(1998)", "(p. 517)" ], "text": "need to be constantly 'on guard' … alert, or mindful of the possibility that the other person is prejudiced" } ], "description": [ { "citation": [], "text": "The greater one's perceived stigma, the greater the need for vigilance in interactions with dominant group members." }, { "citation": [ "Allport (1954)" ], "text": "one of the traits that targets of prejudice develop in defensive coping." }, { "citation": [], "text": "chronic in that it is repeatedly and continually evoked in the everyday life of the minority person." } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "vigilance" }, { "definitions": [ { "citation": [ "Branscombe, Ellemers, Spears, and Doosje (1999)" ], "text": "threat that a person will be categorized by others as a member of a group against his or her will, especially when group membership is irrelevant within the particular context" } ], "description": [], "examples": [ { "citation": [], "text": "categorization as a woman when applying for a business loan" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Categorization threat" }, { "definitions": [ { "citation": [], "text": "undermining of the minority group's values, such as its competence and morality." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Threats to the value of social identity" }, { "definitions": [ { "citation": [], "text": "emerges from negative feedback from one's in-group and the consequent threat rejection by the group." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "threat to acceptance" }, { "definitions": [ { "citation": [ "Steele (1997, p. 614)" ], "text": "social-psychological threat that arises when one is in a situation or doing something for which a negative stereotype about one's group applies" } ], "description": [ { "citation": [], "text": "the emotional reaction to this threat can interfere with intellectual performance." } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "stereotype threat" }, { "definitions": [ { "citation": [], "text": "a member of a stigmatized group removes a domain that is negatively stereotyped (e.g., academic success) from his or her self-definition." } ], "description": [ { "citation": [], "text": "Such disidentification with a goal undermines the person's motivation-and therefore, effort-to achieve in this domain." } ], "examples": [], "related_terms": [ { "citation": [], "text": "stereotype threat" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "disidentification" }, { "definitions": [ { "citation": [], "text": "a form of stress that is internal and insidious." }, { "citation": [ "(e.g., Malyon, 1981–1982)" ], "text": "the internalization of societal antigay attitudes in lesbians and gay men" }, { "citation": [ "(p. 161)" ], "text": "the gay person's direction of negative social attitudes toward the self, leading to a devaluation of the self and resultant internal conflicts and poor self-regard" }, { "citation": [ "(Morris et al., 2001)" ], "text": "the failure of the coming out process to ward off stigma and thoroughly overcome negative self-perceptions and attitudes" } ], "description": [ { "citation": [], "text": "internalized homophobia remains an important factor in the gay person's psychological adjustment throughout life." } ], "examples": [], "related_terms": [], "subtypes": [ { "citation": [], "text": "residual internalized homophobia" } ], "supertypes": [ { "citation": [], "text": "stress process" } ], "synonyms": [], "term": "internalized homophobia" }, { "definitions": [ { "citation": [ "(Cabaj, 1988; Hetrick & Martin, 1984; Malyon, 1981–1982; Nungesser, 1983)" ], "text": "residual antigay attitudes that are integrated into their self-perception" } ], "description": [ { "citation": [ "(Cabaj, 1988; Hetrick & Martin, 1984; Malyon, 1981–1982; Nungesser, 1983)" ], "text": "Gay people maintain varying degrees of residual antigay attitudes that are integrated into their self-perception that can lead to mental health problems" }, { "citation": [ "(p. 117)" ], "text": "Covert forms of internalized homophobia are the most common. Affected individuals appear to accept themselves, yet sabotage their own efforts in a variety of ways" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "internalized homophobia" } ], "synonyms": [], "term": "residual internalized homophobia" }, { "definitions": [ { "citation": [ "(Dohrenwend, Raphael, Schwartz, Stueve, & Skodol, 1993)" ], "text": "stress, in particular life events, as real and observable phenomena that are experienced as stressful because of the adaptational demands they impose on most individuals under similar circumstances" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "subjective view" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "objective view" }, { "definitions": [ { "citation": [], "text": "stress as an experience that depends on the relationship between the individual and his or her environment." } ], "description": [ { "citation": [ "(Lazarus, 1991;Lazarus & Folkman, 1984)" ], "text": "This relationship depends on properties of the external event but also, significantly, on appraisal processes applied by the individual" } ], "examples": [], "related_terms": [ { "citation": [], "text": "objective view" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "subjective view" }, { "definitions": [ { "citation": [ "Link and Phelan (2001)" ], "text": "personal perceived experiences with discrimination" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "structural discrimination" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Individual discrimination" }, { "definitions": [ { "citation": [ "(Link & Phelan, 2001, p. 372)" ], "text": "a wide range of \"institutional practices that work to the disadvantage of … minority groups even in the absence of individual prejudice or discrimination\"" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "Individual discrimination" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "structural discrimination" }, { "definitions": [ { "citation": [ "(Krieger, 2000, p. 63)" ], "text": "how people literally embody and biologically express experiences of racial oppression and resistance, from conception to death, thereby producing racial/ethnic disparities in morbidity and mortality across a wide spectrum of outcomes." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Biological expressions of racial discrimination" }, { "definitions": [ { "citation": [], "text": "explains the higher prevalence of mental disorders as caused by excess in social stressors related to stigma and prejudice." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "minority stress model" }, { "definitions": [ { "citation": [ "(Tajfel & Turner, 1986;Turner, 1999)" ], "text": "the process of categorization (e.g., distinction among social groups) triggers important intergroup processes (e.g., competition and discrimination) and provides an anchor for group and self-definition" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Social identity and self-categorization theories" } ] }, { "paper_id": "057bd5a3a6b652dfd1419128aae578478f5891b0", "split": "original_test", "metadata": { "title": "The Stigma Complex", "authors": [ "B. 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Martin" ], "publication_year": "2015", "doi": "10.1146/annurev-soc-071312-145702", "venue": "The Annual review of sociology" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "a global referent category" }, { "citation": [ "(Goffman 1963, Hinshaw 2006, Sartorius 2007)" ], "text": "the mark, the condition, or status that is subject to devaluation" }, { "citation": [], "text": "the intersection of cultural differentiation, identity formation through social interaction, and social inequality" } ], "description": [ { "citation": [], "text": "Stigma requires (a) distinguishing and labeling differences, (b) associating human differences with negative attributions or stereotypes, (c) separating \"us\" from \"them,\" and (d) experiencing status loss and discrimination." }, { "citation": [], "text": "In sum, a difference is translated into a marked, devalued distinction." } ], "examples": [], "related_terms": [], "subtypes": [ { "citation": [], "text": "experiential variants" }, { "citation": [], "text": "action variants" } ], "supertypes": [], "synonyms": [], "term": "Stigma" }, { "definitions": [ { "citation": [], "text": "the social process by which the mark affects the lives of all those touched by it" } ], "description": [ { "citation": [ "(Link & Phelan 2001, see also Scambler 2009)" ], "text": "dependent on core concerns of the sociological enterprise-power and the ability to stratify tangible and intangible resources" } ], "examples": [], "related_terms": [ { "citation": [], "text": "Stigma" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Stigmatization" }, { "definitions": [ { "citation": [], "text": "negative beliefs and attitudes assigned to social entities thus labeled" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "labels" }, { "citation": [], "text": "prejudice" }, { "citation": [], "text": "discrimination" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "stereotypes" }, { "definitions": [ { "citation": [], "text": "endorsement of stereotypes" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "stereotypes" }, { "citation": [], "text": "discrimination" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "prejudice" }, { "definitions": [ { "citation": [], "text": "differential and disadvantaged treatment of the stigmatized" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "stereotypes" }, { "citation": [], "text": "prejudice" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "discrimination" }, { "definitions": [ { "citation": [], "text": "agreement with a statement that prejudice and discrimination exist toward a labeled group" } ], "description": [ { "citation": [], "text": "It does not necessarily assume an individual's agreement with a stigmatizing statement." } ], "examples": [ { "citation": [], "text": "Sirey et al. (2001) asked nearly 100 individuals newly diagnosed with depression about their perceptions of devaluation and discrimination of individuals with mental illness. They found that younger patients perceived more stigma; however, only older patients' perceptions translated into a discontinuation of treatment within three months." } ], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "experiential variants" } ], "synonyms": [], "term": "Perceived stigma" }, { "definitions": [ { "citation": [], "text": "individuals' or groups' expectations that others will devalue and discriminate against them" } ], "description": [], "examples": [ { "citation": [ "(Franz et al. 2010; see also Lee et al. 2005 on schizophrenia in China, Quinn & Chaudoir 2009 on depression in the United States, Yebei et al. 2008 on HIV/AIDS in Kenya)" ], "text": "fear of the official label of mental illness" }, { "citation": [ "(Vogel et al. 2006)" ], "text": "Among college students, the level of anticipated self-stigma had a direct influence on their predisposition to seek psychological help if confronted with mental health problems" } ], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "experiential variants" } ], "synonyms": [], "term": "Anticipated stigma" }, { "definitions": [ { "citation": [], "text": "expressed agreement with existing stereotypes" } ], "description": [], "examples": [ { "citation": [], "text": "do they agree that most people with the (status/condition) are dangerous, even if they do not apply it to themselves" } ], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "experiential variants" } ], "synonyms": [], "term": "Endorsed stigma" }, { "definitions": [ { "citation": [], "text": "focuses on the stigmatized, asking whether they have personally experienced prejudice and discrimination" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "experiential variants" } ], "synonyms": [], "term": "Received stigma" }, { "definitions": [ { "citation": [], "text": "occurs when individuals behave in a way that prejudices or discriminates against the stigmatized" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "experiential variants" } ], "synonyms": [ { "citation": [], "text": "differential treatment" } ], "term": "enacted stigma" }, { "definitions": [ { "citation": [ "(Boyd Ritsher et al. 2003, Watson et al. 2007)" ], "text": "is faced by the stigmatized, who accept assessments of lower value or worth" } ], "description": [ { "citation": [ "(reviewed in Major & O'Brien 2005)" ], "text": "stigmatized individuals are aware of expectations and act in ways that reinforce prejudice and stereotypes" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "action variants" } ], "synonyms": [], "term": "Self-stigma" }, { "definitions": [ { "citation": [ "(Ostman & Kjellin 2002)" ], "text": "stigma \"by association\"" } ], "description": [ { "citation": [], "text": "Although individuals themselves do not have the mark, they live with, work with, or otherwise have a proximate social relationship with individuals or groups that do." }, { "citation": [], "text": "Because of this social proximity, they too are subjected to devaluation through suspicion of having played a role in cause or the lack of ability to help." } ], "examples": [ { "citation": [ "(Angermeyer et al. 2003, Corrigan & Miller 2004, Koro-Ljungberg & Bussing 2009)" ], "text": "close family and other relatives" }, { "citation": [ "Pontikes et al. (2010)" ], "text": "\"mere association\" with coworkers who had been blacklisted during the Red Scare reduced artists' chances of finding employment." } ], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "action variants" } ], "synonyms": [], "term": "Courtesy stigma" }, { "definitions": [ { "citation": [], "text": "attempts to map the levels and nature of stigma in the general population" } ], "description": [ { "citation": [ "(Pescosolido & Martin 2007)" ], "text": "Public stigma marks the nature of the contextual climate of prejudice and discrimination in time and place" }, { "citation": [], "text": "Levels of public stigma around mental illness remain high, although over the recent period, the public in the Global North (where most research exists) has become more sophisticated in its understanding and more open to recognition and disclosure." } ], "examples": [], "related_terms": [ { "citation": [], "text": "Social Distance" }, { "citation": [], "text": "traditional prejudice" }, { "citation": [], "text": "Exclusionary Sentiments" }, { "citation": [], "text": "negative affect" }, { "citation": [], "text": "Disclosure Carryover" }, { "citation": [], "text": "Perceptions of Dangerousness" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "action variants" } ], "synonyms": [ { "citation": [ "(Quinn & Chaudoir 2009)" ], "text": "cultural stigma" } ], "term": "Public stigma" }, { "definitions": [ { "citation": [ "(2004)", "(p. 481; emphasis added)" ], "text": "includes \"policies of private and governmental institutions that intentionally restrict the opportunities of people\" and \"policies of institutions that yield unintended consequences that hinder the options of people\"" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "action variants" } ], "synonyms": [ { "citation": [ "(Yang et al. 2014, p. 84)" ], "text": "institutional discrimination" } ], "term": "Structural stigma" }, { "definitions": [ { "citation": [], "text": "a desire for social/interpersonal distance" } ], "description": [ { "citation": [], "text": "The logic of this dimension lies in providing venues or roles in which the potential stigmatizer would accept or reject social interaction with either the general category of \"persons with\" or, in the case of the US National General Social Survey studies, a vignette character who meets criteria for specific mental health problems." } ], "examples": [], "related_terms": [ { "citation": [], "text": "Public stigma" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Social Distance" }, { "definitions": [ { "citation": [ "(Bobo et al. 1997, p. 16)" ], "text": "adherence to the belief that blacks are the categorical intellectual inferiors of whites" } ], "description": [ { "citation": [], "text": "A key feature of this form of prejudice is that the stereotypical negative characterization is applied uniformly to all members of the devalued group in the form of stereotypes." } ], "examples": [ { "citation": [ "(see, for example, Couture & Penn 2003)" ], "text": "asking whether individuals with mental illness or specific disorders are as intelligent, productive, or trustworthy as anyone else, or are unpredictable" } ], "related_terms": [ { "citation": [], "text": "Public stigma" } ], "subtypes": [], "supertypes": [], "synonyms": [ { "citation": [], "text": "old-fashioned prejudice" }, { "citation": [], "text": "Jim Crow racism" } ], "term": "traditional prejudice" }, { "definitions": [ { "citation": [], "text": "a stigma dimension that taps into the willingness to exclude persons with mental illness from the full benefits of citizenship, i.e., to deny them the right to engage in certain activities or roles commonly taken for granted by others" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "Public stigma" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Exclusionary Sentiments" }, { "definitions": [ { "citation": [ "(Corrigan et al. 2003, Link et al. 2004)" ], "text": "captures popular public views of how uneasy individuals felt or would feel in an interaction with a person with mental illness" } ], "description": [ { "citation": [], "text": "Are individuals marked by a stigma hard to talk to?" }, { "citation": [], "text": "Does being around stigmatized individuals make individuals feel uncomfortable or nervous?" } ], "examples": [], "related_terms": [ { "citation": [], "text": "Public stigma" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "negative affect" }, { "definitions": [ { "citation": [], "text": "taps into public expectations that persons with discredited conditions or statuses will occupy a devalued position in the community as a result of receiving treatment or other forms of social assistance, subjecting the stigmatized individual to official labeling and public disclosure" } ], "description": [ { "citation": [], "text": "These in turn translate into discriminatory treatment by others in the community, including providers." } ], "examples": [ { "citation": [], "text": "getting treatment would make a person an outsider in the community" }, { "citation": [], "text": "letting others know about receiving treatment would result in the loss of friends" } ], "related_terms": [ { "citation": [], "text": "Public stigma" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Treatment carryover" }, { "definitions": [ { "citation": [], "text": "the negative consequences of disclosure" } ], "description": [ { "citation": [], "text": "have taken on renewed interest, especially at the individual level where the effects of disclosure and the conditions under which it is applied have a positive or negative effect" } ], "examples": [ { "citation": [], "text": "the individual or the family would be better off keeping the situation a secret" }, { "citation": [], "text": "they have little hope of being accepted in the community if the situation is disclosed" } ], "related_terms": [ { "citation": [], "text": "Public stigma" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Disclosure carryover" }, { "definitions": [ { "citation": [ "(see, for example, Link et al. 1999, Pescosolido et al. 1999, Phelan & Link 1998)" ], "text": "based in the public's fear that persons with mental illness represent a threat of potential violence to self and others, are frightening, and represent a public nuisance or threat" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "Public stigma" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Perceptions of Dangerousness" }, { "definitions": [ { "citation": [], "text": "a set of items that, no matter the national context, elicits a prejudicial response from a majority of respondents" } ], "description": [ { "citation": [], "text": "These five items tap various dimensions of stigma described above, in essence, blowing up the standard scale approaches." } ], "examples": [ { "citation": [], "text": "rejecting the individual as a child care provider" }, { "citation": [], "text": "having a potential for violence toward self" }, { "citation": [], "text": "being unpredictable" }, { "citation": [], "text": "rejecting the individual's marriage into the respondent's family" }, { "citation": [], "text": "excluding the individual from teaching children" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "backbone of stigma" }, { "definitions": [ { "citation": [], "text": "the set of interrelated, heterogeneous system structures, from the individual to the society, and processes, from the molecular to the geographic and historical, that constructs, labels, and translates difference into marks" }, { "citation": [], "text": "a system of interrelated, heterogeneous parts that bring together insights across disciplines to provide a more realistic, albeit complicated, sense of the challenge facing the next generation of stigma research" } ], "description": [ { "citation": [], "text": "A stigma complex requires a systems approach to understand the complicated nature and effects of stigma." }, { "citation": [], "text": "Media images, which reify or counter popular stereotypes, and community-based social networks, which function as a mechanism to magnify or dilute larger cultural stereotypes, are also part of the stigma complex." } ], "examples": [], "related_terms": [ { "citation": [], "text": "FINIS" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "stigma complex" } ] }, { "paper_id": "05b3fc81364c2ad10c3b58b3cefcf191f6feb120", "split": "original_test", "metadata": { "title": "Constructing a Climate Change Logic: An Institutional Perspective on the “Tragedy of the Commons”", "authors": [ "S. Ansari", "F. Wijen", "B. Gray" ], "publication_year": "2013", "doi": "10.1287/orsc.1120.0799", "venue": "Organ. 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Bastos", "Dan Mercea" ], "publication_year": "2019", "doi": "10.1177/0894439317734157", "venue": "" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "a false online identity used to voice opinions and manipulate public opinion while pretending to be another person." } ], "description": [ { "citation": [ "(Zheng, Lai, Chow, Hui, & Yiu, 2011)" ], "text": "The term draws from the manipulation of hand puppets using a sock and refers to the remote management of online identities to spread misinformation, promote the work of one individual, endorse a given opinion, target individuals, and challenge a community of users" } ], "examples": [], "related_terms": [ { "citation": [], "text": "bots" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "sockpuppet account" }, { "definitions": [ { "citation": [], "text": "automatic posting protocols" } ], "description": [ { "citation": [], "text": "operating under a fictitious identity" } ], "examples": [], "related_terms": [ { "citation": [], "text": "sockpuppet accounts" } ], "subtypes": [ { "citation": [], "text": "political bots" } ], "supertypes": [], "synonyms": [], "term": "bots" }, { "definitions": [ { "citation": [ "(Bessi & Ferrara, 2016)" ], "text": "the imitation of human activity on social media by computer scripts" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "bot" } ], "synonyms": [], "term": "social bots" }, { "definitions": [ { "citation": [], "text": "bots deployed in a context of polarized political debate." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "bots" } ], "synonyms": [], "term": "political bots" }, { "definitions": [ { "citation": [ "Woolley (2016)" ], "text": "streams of tweets that flood into hashtags used by opponents and are retweeted by bots so as to disrupt the communication and organization of the opposite side." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Twitter \"bombs\"" }, { "definitions": [ { "citation": [], "text": "a supervised network of zombie agents" } ], "description": [], "examples": [ { "citation": [ "(Paulson, 2006)" ], "text": "internet-connected devices" }, { "citation": [ "(Abokhodair, Yoo, & McDonald, 2015)" ], "text": "social media accounts" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "botnet" }, { "definitions": [ { "citation": [], "text": "groups of bots selfreferentially communicating with each other." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "echo chambers" }, { "definitions": [ { "citation": [ "(Benkler, et al., 2017)" ], "text": "news stories that are intentional, misleading half-truths and/or outright lies" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "fake news" }, { "definitions": [ { "citation": [ "(Bastos, 2016)" ], "text": "with a topical emphasis on highly-clickable, shareable, and human-interest driven stories" } ], "description": [ { "citation": [ "(Sunstein, 2001)" ], "text": "viral content that is mostly short, shareable, accessible with mobile devices, and that accentuates polarized identities and balkanizes readerships into like-minded groups" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "hyperpartisan tabloid journalism" }, { "definitions": [ { "citation": [ "(Weedon, Nuland, & Stamos, 2017)" ], "text": "amplify a defined group of user by aggregating and retweeting content tweeted by seed users" } ], "description": [ { "citation": [ "(Weedon, Nuland, & Stamos, 2017)" ], "text": "chiefly orchestrated by \"fake accounts\"" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "false amplification" } ] }, { "paper_id": "0f7eda998bbce003745ff2fdbcaa1d9a8119368b", "split": "train", "metadata": { "title": "ECHO CHAMBERS AND EPISTEMIC BUBBLES", "authors": [ "C. Nguyen" ], "publication_year": "2018", "doi": "10.1017/epi.2018.32", "venue": "Episteme" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "a social epistemic structure in which other relevant voices have been left out, perhaps accidentally." }, { "citation": [], "text": "a social epistemic structure in which some relevant voices have been excluded through omission." }, { "citation": [], "text": "a social epistemic structure which has inadequate coverage through a process of exclusion by omission." }, { "citation": [], "text": "An epistemic bubble is an epistemic structure emerging from the informational architecture of communities, social networks, media, and other sources of information and argument." }, { "citation": [], "text": "Epistemic bubbles are those structures which omit relevant voices by any means, technological or otherwise." } ], "description": [ { "citation": [], "text": "Members of epistemic bubbles lack exposure to relevant information and arguments." }, { "citation": [], "text": "Epistemic bubbles can form with no ill intent, through ordinary processes of social selection and community formation." }, { "citation": [], "text": "It is an impaired informational topology -a structure with poor connectivity." }, { "citation": [], "text": "Mere exposure to evidence can shatter an epistemic bubble" }, { "citation": [], "text": "That omission need not be malicious or even intentional, but members of that community will not receive all the relevant evidence, nor be exposed to a balanced set of arguments." } ], "examples": [ { "citation": [ "(Bishop 2009)" ], "text": "physically sorting oneself into neighborhoods of like-minded people" } ], "related_terms": [ { "citation": [], "text": "echo chambers" } ], "subtypes": [ { "citation": [], "text": "filter bubbles" } ], "supertypes": [ { "citation": [], "text": "social epistemic structure" } ], "synonyms": [], "term": "epistemic bubble" }, { "definitions": [ { "citation": [], "text": "a social epistemic structure from which other relevant voices have been actively excluded and discredited." }, { "citation": [ "(76)" ], "text": "an echo chamber is a bounded and enclosed group that magnifies the internal voices and insulates them from rebuttal" }, { "citation": [], "text": "an epistemic community which creates a significant disparity in trust between members and non-members." }, { "citation": [], "text": "an epistemic structure created through the manipulation of trust; 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Anikina", "R. Berganza", "Incilay Cangoz", "M. Coman", "B. Hamada", "F. Hanusch", "Christopher D. Karadjov", "C. Mellado", "Sonia Virginia Moreira", "Peter G. Mwesige", "P. Plaisance", "Z. Reich", "Josef Seethaler", "Elizabeth A. 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King", "Jun He" ], "publication_year": "2005", "doi": "10.17705/1cais.01632", "venue": "Communications of the Association for Information Systems" }, "definition_records": [ { "definitions": [ { "citation": [ "[Begg and Berlin, 1988]" ], "text": "the observation that significant results are more likely to be published while non-significant results tend to be relegated to file drawers." } ], "description": [ { "citation": [], "text": "the meta-analysis result will focus on an unrepresentative proportion of a total research population." }, { "citation": [], "text": "Using an unrepresentative set of data may result in conclusions biased toward significance or positivity." } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [ { "citation": [ "[Rosenthal, 1979;Iyengar and Greenhouse, 1988]" ], "text": "file-drawer problem" } ], "term": "Publication bias" }, { "definitions": [ { "citation": [], "text": "aggregating results derived from studies with incommensurable research goals, measures, and procedures." } ], "description": [ { "citation": [], "text": "This problem exists for all review methods, qualitative or quantitative" } ], "examples": [], "related_terms": [ { "citation": [], "text": "meta-analysis" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "apples and oranges" } ] }, { "paper_id": "167f1d5e64b874bea86acdef6d5476da904fec6a", "split": "train", "metadata": { "title": "Confirmation, Disconfirmation, and Information in Hypothesis Testing", "authors": [ "J. 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Ha" ], "publication_year": "1987", "doi": "10.1037/0033-295x.94.2.211", "venue": "" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "people tend to test those cases that have the best chance of verifying current beliefs rather than those that have the best chance of falsifying them" }, { "citation": [], "text": "a tendency to test cases known to be targets rather than those known to be nontargets" } ], "description": [ { "citation": [], "text": "confirmation bias has meant different things to different investigators" }, { "citation": [], "text": "many phenomena labeled \"confirmation bias\" are better understood in terms of a general positive test strategy" } ], "examples": [ { "citation": [], "text": "people are overly influenced by the co-occurrence of two events and insufficiently influenced by instances in which one event occurs without the other" } ], "related_terms": [ { "citation": [], "text": "positive test strategy" }, { "citation": [], "text": "seeking 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"text": "examine instances that you predict will not have the target property" }, { "citation": [], "text": "examine instances you most expect to falsify, rather than verify, your hypothesis" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "falsification" }, { "citation": [], "text": "disconfirmation" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "seeking disconfirmation" }, { "definitions": [ { "citation": [], "text": "verify the hypothesis, in the sense of providing favorable evidence" } ], "description": [ { "citation": [], "text": "The hypothesis may be correct, but these instances can occur even if the hypothesis is not correct." }, { "citation": [], "text": "verifications must also be considered informative, despite their logical ambiguity" } ], "examples": [], "related_terms": [ { "citation": [], "text": "falsification" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "verification" }, { "definitions": [ { "citation": [], "text": "falsifications are not conclusive but merely constitute some evidence against the hypothesis" } ], "description": [ { "citation": [], "text": "Note that there are only conclusive falsifications, no conclusive verifications." } ], "examples": [], "related_terms": [ { "citation": [], "text": "verification" }, { "citation": [], "text": "seeking disconfirmation" } ], "subtypes": [ { "citation": [], "text": "conclusive falsifications" } ], "supertypes": [], "synonyms": [], "term": "falsification" }, { "definitions": [ { "citation": [], "text": "the subject's goal is to identify the rule or concept that determines which of a subset of stimuli are designated as correct." } ], "description": [ { "citation": [], "text": "the set of possible instances and possible rules is highly restricted." } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "laboratory rule-discovery task" } ], "synonyms": [ { "citation": [], "text": "concept identification" } ], "term": "concept-identification task" } ] }, { "paper_id": "17734113f254a64b3bae312713edba3b1e34fb56", "split": "original_test", "metadata": { "title": "The Emergence of Deepfake Technology: A Review", "authors": [ "M. Westerlund" ], "publication_year": "2019", "doi": "10.22215/timreview/1282", "venue": "Technology Innovation Management Review" }, "definition_records": [ { "definitions": [ { "citation": [ "(Aldwairi & Alwahedi, 2018;Jang & Kim, 2018)" ], "text": "fictitious news style content that is fabricated to deceive the public" } ], "description": [ { "citation": [ "(Borges et al., 2018;Qayyum et al., 2019)" ], "text": "In recent years, fake news has become an issue that is a threat to public discourse, human society, and democracy" } ], "examples": [], "related_terms": [ { "citation": [ "(CNN06)" ], "text": "deepfakes" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Fake news" }, { "definitions": [ { "citation": [ "(Anderson, 2018;Qayyum et al., 2019;Zannettou et al., 2019)" ], "text": "digital disinformation and information warfare led by malevolent actors running false information campaigns to manipulate public opinion" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "\"post-truth\" era" }, { "definitions": [ { "citation": [ "(Chawla, 2019)" ], "text": "hyper-realistic videos using face swaps that leave little trace of manipulation" }, { "citation": [ "(Maras & Alexandrou, 2018)" ], "text": "the product of artificial intelligence (AI) applications that merge, combine, replace, and superimpose images and video clips to create fake videos that appear authentic" }, { "citation": [], "text": "hyper-realistic videos that apply artificial intelligence (AI) to depict someone say and do things that never happened" }, { "citation": [ "(CNN03; FRB04)" ], "text": "hyper-realistic videos digitally manipulated to depict people saying and doing things that never actually happened" } ], "description": [ { "citation": [ "(CNN03; FRB04)" ], "text": "A combination of \"deep learning\" and \"fake\"" }, { "citation": [ "(CBS02; PCM10)" ], "text": "Deepfakes rely on neural networks that analyze large sets of data samples to learn to mimic a person's facial expressions, mannerisms, voice, and inflections" }, { "citation": [ "(PCM01)" ], "text": "The process involves feeding footage of two people into a deep learning algorithm to train it to swap faces" }, { "citation": [ "(FOX09; PCM03)" ], "text": "In other words, deepfakes use facial mapping technology and AI that swaps the face of a person on a video into the face of another person" }, { "citation": [ "(FRB05; WP01)" ], "text": "Deepfakes are difficult to detect, as they use real footage, can have authentic-sounding audio, and are optimized to spread on social media quickly" }, { "citation": [], "text": "These fakes of real people are often highly viral and tend to spread quickly through social media platforms, thus making them an efficient tool for disinformation." }, { "citation": [], "text": "Deepfakes are a major threat to our society, political system, and business because they 1) put pressure on journalists struggling to filter real from fake news, 2) threaten national security by disseminating propaganda and interfering in elections, 3) hamper citizen trust toward information by authorities, and, 4) raise cybersecurity issues for people and organizations." } ], "examples": [ { "citation": [ "(Day, 2018;Fletcher, 2018)" ], "text": "a humorous, pornographic, or political video of a person saying anything, without the consent of the person whose image and voice is involved" }, { "citation": [ "(Hasan & Salah, 2019)" ], "text": "political leaders, actresses, comedians, and entertainers having their faces weaved into porn videos" }, { "citation": [ "(CNET05; PCM10)" ], "text": "Nicolas Cage acting in movies in which he has never starred in, such as Indiana Jones or Terminator 2" }, { "citation": [ "(CNET01; FRB06)" ], "text": "a video that replaces Alden Ehrenreich with young Harrison Ford in clips taken from Solo: A Star Wars Story" }, { "citation": [ "(CNET01; FRB06)" ], "text": "a video of actor Bill Hader appearing on Late Night with David Letterman. 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Yu" ], "publication_year": "2019", "doi": "10.1109/tnnls.2020.2978386", "venue": "IEEE Transactions on Neural Networks and Learning Systems" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "A syntactic dependency tree defines the syntactic relations among words in a sentence." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "syntactic relations" }, { "citation": [], "text": "words" }, { "citation": [], "text": "sentence" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "syntactic dependency tree" } ] }, { "paper_id": "1ccc69b50a7495af1547833415f89536619c93e9", "split": "train", "metadata": { "title": "The Dynamics of Public Attention: Agenda-Setting Theory Meets Big Data", "authors": [ "W. Neuman", "Lauren Guggenheim", "S. M. Jang", "S. Bae" ], "publication_year": "2014", "doi": "10.1111/jcom.12088", "venue": "" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "the dynamics of attention to issues over time" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "reverse agenda-setting" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "agenda setting" }, { "definitions": [ { "citation": [ "Chong (1993, p. 870)" ], "text": "the distillation or sorting out of frames of reference on political issues" } ], "description": [ { "citation": [ "Chong (1993, p. 870)" ], "text": "New issues in the public eye are typically subject to a variety of interpretations." }, { "citation": [ "Chong (1993, p. 870)" ], "text": "In the course of public debate, however, public opinion leaders establish common frames of reference for discussing the issue and 'neutralize,' or render irrelevant, alternative interpretations." } ], "examples": [ { "citation": [ "(Gilens, 1999;Iyengar, 1991)" ], "text": "The classic exemplar concerning the framing of the unemployment issue, for example, contrasts an issue frame emphasizing ill-prepared workers lacking in job skills with structural and industrial policy problems in an increasingly global economy" }, { "citation": [], "text": "the relative emphasis in the discussion of gun legislation on constitutional rights or alternatively on safety" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "framing" }, { "definitions": [ { "citation": [ "(Golan, 2006)" ], "text": "the effects of institutional media agendas on each other" } ], "description": [ { "citation": [ "(Denham, 2010, p. 315)" ], "text": "A number of studies attribute intermedia communication processes to common interests and sources among journalists (e.g., pack journalism) as well as news organizations' willingness to \"report on a report\"" } ], "examples": [ { "citation": [ "(Golan, 2006)" ], "text": "the correlation of the agendas of three evening television programs with that of the New York Times the following morning" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "intermedia agenda building" }, { "definitions": [ { "citation": [ "Bennett's (1990)" ], "text": "coverage of policy issues predominantly in terms of official sources" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "media \"indexing\"" }, { "definitions": [ { "citation": [], "text": "telling its readers what to think about" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "media agenda-setting" }, { "definitions": [ { "citation": [], "text": "the same-day covariations among social and traditional media without any lags" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "raw correlations" }, { "definitions": [ { "citation": [ "(Chong & Druckman, 2007;Entman, 1993)" ], "text": "how the issue is framed and which issue attributes are emphasized" } ], "description": [], "examples": [ { "citation": [ "(Gilens, 1999;Iyengar, 1991)" ], "text": "an issue frame emphasizing ill-prepared workers lacking in job skills with structural and industrial policy problems in an increasingly global economy" }, { "citation": [], "text": "the relative emphasis in the discussion of gun legislation on constitutional rights or alternatively on safety" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [ { "citation": [], "text": "framing research" } ], "term": "second-level agenda setting" } ] }, { "paper_id": "1fc22db1adfbc21daef99f3199de1e5c8f05be09", "split": "train", "metadata": { "title": "How Elite Partisan Polarization Affects Public Opinion Formation", "authors": [ "James N. Druckman", "E. Peterson", "Rune Slothuus" ], "publication_year": "2013", "doi": "10.1017/s0003055412000500", "venue": "American Political Science Review" }, "definition_records": [ { "definitions": [ { "citation": [ "Schattschneider (1960, 138)" ], "text": "a competitive political system in which competing leaders and organizations define the alternatives of public policy in such a way that the public can participate in the decision-making process" } ], "description": [ { "citation": [], "text": "Competition is a defining element of even the most minimalist conceptions of democracy." } ], "examples": [], "related_terms": [ { "citation": [], "text": "political competition" }, { "citation": [], "text": "public policy" }, { "citation": [], "text": "decision-making process" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "democracy" }, { "definitions": [ { "citation": [], "text": "high levels of ideological distance between parties and high levels of homogeneity within parties." }, { 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describes a hate group rally in terms of free speech, then the audience will subsequently base its opinions about the rally on free speech considerations and support the right to rally." }, { "citation": [ "(Nelson, Clawson, and Oxley 1997)" ], "text": "if the speaker uses a public safety frame, the audience will base its opinions on public safety considerations and oppose the rally" } ], "related_terms": [ { "citation": [], "text": "Frames" }, { "citation": [], "text": "frame strength" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "framing effect" }, { "definitions": [ { "citation": [], "text": "a relative construct that refers to individuals' perceptions of what makes a compelling argument." }, { "citation": [ "Chong and Druckman 2007" ], "text": "A frame is deemed relatively stronger than another if it receives a significantly higher rating of effectiveness or applicability" } ], "description": [ { "citation": [], "text": "strength is based on perceptions and not normatively derived criteria per se." }, { "citation": [], "text": "Different frames on each side might be relatively strong or weak when compared to one another." } ], "examples": [ { "citation": [], "text": "For example, individuals likely perceive the public safety frame to be a stronger argument against a hate group's rally than an alternative \"con\" frame that argues that the rally should not be held because it will result in litter in the streets." } ], "related_terms": [ { "citation": [], "text": "Frames" }, { "citation": [], "text": "effectiveness" }, { "citation": [], "text": "applicability" } ], "subtypes": [], "supertypes": [], "synonyms": [ { "citation": [ "(e.g., O'Keefe 2002, 147, 156)" ], "text": "argument strength" } ], "term": "frame strength" }, { "definitions": [ { "citation": [ "Bullock (2011, 496)" ], "text": "positiontaking by party elites" } ], "description": [ { "citation": [], "text": "an endorsement is only one type of cue." }, { "citation": [ "Bullock (2011)" ], "text": "cues and frames almost always appear together: Party elites rarely take a position without trying to frame it in a way that will garner support for it" } ], "examples": [], "related_terms": [ { "citation": [], "text": "Frames" }, { "citation": [], "text": "opinion formation" }, { "citation": [], "text": "partisan motivated reasoning" } ], "subtypes": [ { "citation": [], "text": "endorsement" } ], "supertypes": [], "synonyms": [ { "citation": [], "text": "party endorsements" } ], "term": "party cue" }, { "definitions": [ { "citation": [], "text": "the tendency to seek out information that confirms prior beliefs (i.e., a confirmation bias), view evidence consistent with prior opinions as stronger or more effective (i.e., a prior attitude effect), and spend more time arguing and dismissing evidence inconsistent with prior opinions, regardless of objective accuracy (i.e., a disconfirmation bias)." } ], "description": [ { "citation": [], "text": "These biases influence the reception of new information and may lead individuals to \"reason\" their way to a desired conclusion." }, { "citation": [ "(e.g., Kunda 1990, 485; also see Nir 2011;Prior 2007)" ], "text": "When individuals are highly motivated to form accurate opinions, they tend to focus on substance regardless of their partisanship and/or prior opinions" } ], "examples": [], "related_terms": [ { "citation": [], "text": "confirmation bias" }, { "citation": [], "text": "prior attitude effect" }, { "citation": [], "text": "disconfirmation bias" } ], "subtypes": [ { "citation": [], "text": "partisan motivated reasoning" } ], "supertypes": [], "synonyms": [ { "citation": [ "Taber and Lodge's (2006)" ], "text": "motivated skepticism" }, { "citation": [ "Lavine, Johnston, and Steenbergen's (2012)" ], "text": "partisan perceptional screen" } ], "term": "Motivated reasoning" }, { "definitions": [ { "citation": [], "text": "the tendency to seek out information that confirms prior beliefs" } ], 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[ { "citation": [], "text": "the tendency for parties to arrive at judgments that reflect a self-serving bias-to conflate what is fair with what benefits oneself." } ], "description": [ { "citation": [], "text": "The bias is also present when bargainers have incentives to evaluate the situation impartially, which implies that the bias does not appear to be deliberate or strategic." }, { "citation": [], "text": "The self-serving bias affects not only individuals' evaluations of themselves, but also of groups they are affiliated with." }, { "citation": [ "(Dunning, Meyerowitz and Holzberg, 1989)", "(Darley and Gross, 1983)" ], "text": "the bias results from selective information processing." }, { "citation": [], "text": "the self-serving bias is an important determinant of bargaining impasse." } ], "examples": [ { "citation": [ "(Ross and Sicoly, 1979)" ], "text": "when married couples estimate the fraction of various household tasks they are responsible for, their estimates typically 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[ { "citation": [ "{McCarthy, 1996 #xxx}" ], "text": "bias in the media's recording of protest events" } ], "synonyms": [], "term": "Selection bias" }, { "definitions": [ { "citation": [ "{McCarthy, 1996 #xxx}" ], "text": "Description bias reflects agenda-building processes, and it introduces another distinct way in which media personnel shape the political messages conveyed in their news reports by making choices about how a protest event is portrayed in a media story." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "agenda-building" }, { "citation": [ "{McCarthy, 1996 #xxx}" ], "text": "selection bias" } ], "subtypes": [], "supertypes": [ { "citation": [ "{McCarthy, 1996 #xxx}" ], "text": "bias in the media's recording of protest events" } ], "synonyms": [], "term": "Description bias" }, { "definitions": [ { "citation": [ "{Ryan 1990 #xxx : 22-25}" ], "text": "models, which explain media routines according to broad socioeconomic forces including 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"episodic framing depicts concrete events that illustrate issues" } ], "description": [ { "citation": [], "text": "the episodic frame through which many public protests are portrayed leads consumers of mass media away from systemic explanations for the problems protesters are seeking to address" }, { "citation": [ "{Iyengar, 1991 :141, 143}" ], "text": "In the long run, episodic framing contributes to the trivialization of public discourse and the erosion of electoral accountability." } ], "examples": [ { "citation": [], "text": "an individual welfare mother" }, { "citation": [], "text": "a terrorist bombing" } ], "related_terms": [ { "citation": [], "text": "thematic news frames" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "news stories" } ], "synonyms": [], "term": "Episodic news frames" }, { "definitions": [ { "citation": [], "text": "thematic news frames provide information that helps contextualize social problems, focusing more on general trends and conditions 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Ross" ], "publication_year": "2002", "doi": "10.2307/3333623", "venue": "" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "not only does propaganda involve persuading, but also the one who is persuading (Sender) is doing so intentionally, and moreover there is a target for such persuasion (Receiver) and a means of reaching that target (Message)." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "Sender" }, { "citation": [], "text": "Receiver" }, { "citation": [], "text": "Message" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "communication model of Sender-Message-Receiver" }, { "definitions": [ { "citation": [ "3" ], "text": "any attempt to persuade anyone of any belief." }, { "citation": [ "4" ], "text": "an expression of opinion or action by individuals or groups deliberately designed to influence the opinions and actions of other individuals or groups with reference to a predetermined end." }, { "citation": [ "5" ], "text": "an expression overtly set forth or covertly implied in order to influence the attitudes and through the attitudes, the opinions and action of a public." }, { "citation": [ "6" ], "text": "an attempt to influence public opinion and conduct — especially social opinion and conduct — in such a manner that the persons who adopt the opinions and behaviors do so without themselves making any definite search for reasons." }, { "citation": [ "7" ], "text": "activities and communications from a government to its own citizens, other governmental personnel, or foreign audiences in general." }, { "citation": [], "text": "an epistemically defective message used with the intention to persuade a socially significant group of people on behalf of a political institution, organization, or cause." } ], "description": [ { "citation": [], "text": "propaganda is in some sense intentional." }, { "citation": [], "text": "Propaganda involves the intention to persuade." }, { "citation": [], "text": "propaganda is sent on behalf of a political institution organization or cause." }, { "citation": [], "text": "propaganda must be aimed at a group." }, { "citation": [], "text": "Epistemic defectiveness captures the role that the emotions play in propaganda as well as commands, conceptual schemes and metaphors." } ], "examples": [ { "citation": [ "17" ], "text": "the French's claims in World War I that the Germans ate babies" }, { "citation": [ "17" ], "text": "the claims that Iraqi soldiers dumped prematurely born infants out of their incubators" }, { "citation": [], "text": "On the other hand, Jonathan Swift's A Modest Proposal is propaganda since he uses satire on behalf of the Irish in order to protest taxation laws that were oppressing poor people." } ], "related_terms": [ { "citation": [ "3" ], "text": "persuasion" }, { "citation": [], "text": "epistemic defectiveness" }, { "citation": [], "text": "intention to persuade" }, { "citation": [], "text": "socially significant group of people" }, { "citation": [], "text": "political institution, organization, or cause" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "propaganda" }, { "definitions": [ { "citation": [], "text": "being political, in the garden variety sense of the word, involves, minimally, partisanship and a preoccupation with a conception of justice or social order." } ], "description": [], "examples": [ { "citation": [], "text": "candidates running for political office" }, { "citation": [], "text": "countries involved in a war effort" }, { "citation": [], "text": "Planned Parenthood" }, { "citation": [], "text": "Right to Life" }, { "citation": [], "text": "English First" }, { "citation": [], "text": "Greenpeace" }, { "citation": [], "text": "The Grey Panthers" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "political" }, { "definitions": [ { "citation": [], "text": "lying entails x's uttering a statement that x believes to be false with the intention of leading an audience y to believe it to be true." } ], "description": [ { "citation": [], "text": "There are two separate claims wrapped in the view that pieces of propaganda are lies. 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This ad is epistemically defective because it spuriously leads its audience to believe that Harvey Gantt (perhaps, because he's an African American) supports morally objectionable racial quotas." }, { "citation": [], "text": "white hands ad" } ], "related_terms": [ { "citation": [], "text": "propaganda" } ], "subtypes": [ { "citation": [], "text": "inapt metaphors" } ], "supertypes": [], "synonyms": [], "term": "epistemic defectiveness" }, { "definitions": [ { "citation": [], "text": "(1) an epistemically defective message (2) used with the intention to persuade (3) the beliefs, opinions, desires, and behaviors of a socially significant group of people (4) on behalf of a political organization, institution, or cause." } ], "description": [ { "citation": [], "text": "the four conditions work together to limit the scope of propaganda." }, { "citation": [], "text": "it has isolated conceptually propaganda from other communications, and given us a framework within which we can discuss our disagreements about particular cases." } ], "examples": [], "related_terms": [ { "citation": [], "text": "propaganda" }, { "citation": [], "text": "epistemic defectiveness" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "epistemic merit model" }, { "definitions": [ { "citation": [], "text": "His term \"doublespeak\" captures how ambiguous referents can create a true statement but an epistemically defective message." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "epistemic defectiveness" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "doublespeak" } ] }, { "paper_id": "23eb7b57f821ec3b579605540b494d7c079a8467", "split": "train", "metadata": { "title": "Beyond prejudice as simple antipathy: Hostile and benevolent sexism across cultures.", "authors": [ "Peter M. Glick", "S. Fiske", "A. Mladinic", "José L. Saiz", "Dominic Abrams", "Barbara M. Masser", "B. Adetoun", "J. E. Osagie", "Adebowale Akande", "A. Alao", "Barbara Annetje", "T. Willemsen", "K. Chipeta", "Benoit Dardenne", "A. Dijksterhuis", "D. Wigboldus", "Thomas Eckes", "Iris Six-Materna", "Francisca Expósito", "Miguel Moya", "M. Foddy", "Hyun Jeong Kim", "M. Lameiras", "María José Sotelo", "Angelica Mucchi-Faina", "M. Romani", "Nuray Sakallı", "Bola Udegbe", "Mariko Yamamoto", "M. Ui", "Maria C. 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"text": "a mythic story which posits that 'with effort, hard work, optimism, and egalitarian cooperation, anyone in America can morally achieve material success [emphasis original]'" } ], "description": [ { "citation": [ "(Ashton 2009a)" ], "text": "the freedom to get good jobs and obtain 'the basics of American life, such as buying car insurance'" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "American Dream" }, { "definitions": [ { "citation": [], "text": "frame the news in a way that focuses on how issues affect particular people." } ], "description": [ { "citation": [ "(Semetko and Valkenburg 2000)" ], "text": "the goal of human interest stories is to personalize and emotionalize an event, issue or problem by helping the audience personally connect to an individual or individuals who represent the issue" } ], "examples": [], "related_terms": [ { "citation": [ "(Semetko and Valkenburg 2000)" ], "text": "human interest frame" } ], 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expression of the speaker or writer's attitude or stance towards, viewpoint on, or feelings about the entities or propositions that he or she is talking about." }, { "citation": [ "(Labov and Waletzky 1997[1967], Labov 1972)" ], "text": "the features of a narrative whose function is to underscore the extraordinary quality of the represented events and hence the conversational value of the telling." } ], "description": [ { "citation": [ "(6-13)" ], "text": "expressing the opinion of the speaker/writer vis à vis the propositions being expressed, manipulating the hearer/reader's attitude vis à vis these propositions (in part by constructing and maintaining relationships between speaker/writer and hearer/reader), and organizing the discourse, for example, by marking boundaries or highlighting significant parts" }, { "citation": [], "text": "Because evaluating a proposition often involves comparing it against a norm, linguistic features associated with evaluation may include such things as 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attributes obtained from user connections, activities, or interactions differ and misrepresent the true behavior of the users" } ], "description": [ { "citation": [ "[59,107]" ], "text": "The differences and biases in the networks can be a result of many factors, such as network sampling" } ], "examples": [ { "citation": [ "[101]" ], "text": "authors show how social networks can be biased toward low-degree nodes when only considering the links in the network and not considering the content and behavior of users in the network." }, { "citation": [ "[149]" ], "text": "user interactions are significantly different from social link patterns that are based on features, such as method of interaction or time." } ], "related_terms": [ { "citation": [], "text": "network attributes" }, { "citation": [], "text": "network sampling" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Linking Bias" }, { "definitions": [ { "citation": [ "[140]" ], "text": "Measurement, or reporting, bias arises from how we choose, utilize, and measure particular features" } ], "description": [], "examples": [ { "citation": [ "[140]" ], "text": "An example of this type of bias was observed in the recidivism risk prediction tool COMPAS, where prior arrests and friend/family arrests were used as proxy variables to measure level of \"riskiness\" or \"crime\"-which on its own can be viewed as mismeasured proxies. This is partly due to the fact that minority communities are controlled and policed more frequently, so they have higher arrest rates. However, one should not conclude that because people coming from minority groups have higher arrest rates, therefore they are more dangerous, as there is a difference in how these groups are assessed and controlled" } ], "related_terms": [ { "citation": [], "text": "proxy variables" }, { "citation": [], "text": "features" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Measurement Bias" }, { "definitions": [ { "citation": [ "[38,110,127]" ], "text": "one or more important variables are left out of the model" } ], "description": [], "examples": [ { "citation": [], "text": "The appearance of the competitor was something that the model was not ready for; therefore, it is considered to be an omitted variable." } ], "related_terms": [ { "citation": [], "text": "model" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Omitted Variable Bias" }, { "definitions": [ { "citation": [], "text": "Items that are more popular tend to be exposed more." } ], "description": [ { "citation": [ "[113]" ], "text": "popularity metrics are subject to manipulation-for example, by fake reviews or social bots" } ], "examples": [], "related_terms": [ { "citation": [], "text": "popularity metrics" }, { "citation": [], "text": "recommendation systems" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Popularity Bias" }, { "definitions": [ { "citation": [ "[116]" ], "text": "statistics, demographics, representatives, and user characteristics are different in the user population of the platform from the original target population" } ], "description": [ { "citation": [], "text": "Population bias creates non-representative data." } ], "examples": [ { "citation": [], "text": "An example of this type of bias can arise from different user demographics on different social platforms, such as women being more likely to use Pinterest, Facebook, Instagram, while men being more active in online forums like Reddit or Twitter." } ], "related_terms": [ { "citation": [], "text": "user population" }, { "citation": [], "text": "target population" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Population Bias" }, { "definitions": [ { "citation": [ "[9]" ], "text": "a result of how information is presented" } ], "description": [ { "citation": [], "text": "on the Web users can only click on content that they see, so the seen content gets clicks, while everything else gets no click." } ], "examples": [ { "citation": [ "[9]" ], "text": "For example, on the Web users can only click on content that they see, so the seen content gets clicks, while everything else gets no click. And it could be the case that the user does not see all the information on the Web" } ], "related_terms": [ { "citation": [], "text": "User Interaction bias" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Presentation Bias" }, { "definitions": [ { "citation": [], "text": "traits identified by law on which it is illegal to discriminate against" } ], "description": [ { "citation": [], "text": "these traits that are considered to be \"protected\" or \"sensitive\" attributes in computer science literature." } ], "examples": [], "related_terms": [ { "citation": [], "text": "Direct discrimination" }, { "citation": [], "text": "decision-making process" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "traits" } ], "synonyms": [ { "citation": [], "text": "sensitive attributes" } ], "term": "protected attributes" }, { "definitions": [ { "citation": [ "[82]" ], "text": "A variable V in a causal graph exhibits potential proxy discrimination, if there exists a directed path from A to V that is blocked by a proxy variable and V itself is not a proxy" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "causal graph" }, { "citation": [], "text": "proxy variable" }, { "citation": [ "[82]" ], "text": "Unresolved Discrimination" } ], "subtypes": [], "supertypes": [ { "citation": [ "[82]" ], "text": "discrimination" } ], "synonyms": [], "term": "Proxy Discrimination" }, { "definitions": [ { "citation": [], "text": "The idea that top-ranked results are the most relevant and important will result in attraction of more clicks than others." } ], "description": [ { "citation": [ "[9]" ], "text": "This bias affects search engines" } ], "examples": [], "related_terms": [ { "citation": [], "text": "top-ranked results" }, { "citation": [], "text": "User Interaction bias" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Ranking Bias" }, { "definitions": [ { "citation": [ "[140]" ], "text": "how we sample from a population during data collection process" } ], "description": [ { "citation": [], "text": "Non-representative samples lack the diversity of the population, with missing subgroups and other anomalies." } ], "examples": [], "related_terms": [ { "citation": [], "text": "Sampling Bias" }, { "citation": [], "text": "Non-representative samples" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Representation Bias" }, { "definitions": [ { "citation": [], "text": "Sampling bias is similar to representation bias, and it arises due to non-random sampling of subgroups." } ], "description": [ { "citation": [], "text": "As a consequence of sampling bias, the trends estimated for one population may not generalize to data collected from a new population." } ], "examples": [], "related_terms": [ { "citation": [], "text": "representation bias" }, { "citation": [], "text": "non-random sampling" } ], "subtypes": [ { "citation": [], "text": "Self-selection bias" } ], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Sampling Bias" }, { "definitions": [ { "citation": [], "text": "a subtype of the selection or sampling bias in which subjects of the research select themselves." } ], "description": [], "examples": [ { "citation": [], "text": "an opinion poll to measure enthusiasm for a political candidate, where the most enthusiastic supporters are more likely to complete the poll." } ], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "sampling bias" }, { "citation": [], "text": "selection bias" } ], "synonyms": [], "term": "Self-selection Bias" }, { "definitions": [ { "citation": [ "[18]" ], "text": "a type of aggregation bias that arises in the analysis of heterogeneous data" }, { "citation": [], "text": "an association observed in aggregated data disappears or reverses when the same data is disaggregated into its underlying subgroups" } ], "description": [ { "citation": [ "[37]" ], "text": "Simpson's paradox has been observed in a variety of domains, including biology" } ], "examples": [ { "citation": [ "[16]" ], "text": "One of the better-known examples of the type of paradox arose during the gender bias lawsuit in university admissions against UC Berkeley [16]. After\nanalyzing graduate school admissions data, it seemed like there was bias toward women, a smaller fraction of whom were being admitted to graduate programs compared to their male counterparts. However, when admissions data was separated and analyzed over the departments, women applicants had equality and in some cases even a small advantage over men. The paradox happened as women tended to apply to departments with lower admission rates for both genders. " } ], "related_terms": [ { "citation": [], "text": "aggregated data" }, { "citation": [], "text": "subgroups" } ], "subtypes": [], "supertypes": [ { "citation": [ "[18]" ], "text": "aggregation bias" } ], "synonyms": [], "term": "Simpson's Paradox" }, { "definitions": [ { "citation": [ "[9]" ], "text": "Social bias happens when others' actions affect our judgment" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "others' actions" }, { "citation": [], "text": "judgment" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Social Bias" }, { "definitions": [ { "citation": [], "text": "Tries to move as little as possible to retain its similarity to the original embedding as much as possible, while reducing the gender bias." } ], "description": [ { "citation": [ "[20]" ], "text": "This tradeoff is controlled by a parameter" } ], "examples": [], "related_terms": [ { "citation": [], "text": "original 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"term": "Statistical Discrimination" }, { "definitions": [ { "citation": [], "text": "Subgroup fairness intends to obtain the best properties of the group and individual notions of fairness." } ], "description": [ { "citation": [], "text": "It is different than these notions but uses them to obtain better outcomes." }, { "citation": [ "[79,80]" ], "text": "It picks a group fairness constraint like equalizing false positive and asks whether this constraint holds over a large collection of subgroups" } ], "examples": [], "related_terms": [ { "citation": [], "text": "group fairness" }, { "citation": [], "text": "individual notions of fairness" }, { "citation": [], "text": "group" }, { "citation": [], "text": "individual" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "fairness" } ], "synonyms": [], "term": "Subgroup Fairness" }, { "definitions": [ { "citation": [ "[40]" ], "text": "policies, customs, or behaviors that are a part of the culture or structure of an 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Zuiderveen Borgesius", "Damian Trilling", "Judith Möller", "Balázs Bodó", "Claes H. de Vreese", "Natali Helberger" ], "publication_year": "2016", "doi": "10.14763/2016.1.401", "venue": "Internet Policy Review" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "the phenomenon that media content is not the same for every user, but tailored to different groups or individuals." } ], "description": [ { "citation": [ "(e.g., Pariser, 2011;Sunstein, 2002)" ], "text": "personalised content and services could limit the diversity of media content people are exposed to and thus have an adverse effect on the democratic discourse, open-mindedness and a healthy public sphere" } ], "examples": [ { "citation": [], "text": "a personalised news website could give more prominence to conservative or liberal media items, based on the (assumed) political interests of the user." } ], "related_terms": [], "subtypes": [ { "citation": [], "text": "self-selected personalisation" }, { "citation": [], "text": "pre-selected personalisation" } ], "supertypes": [], "synonyms": [], "term": "personalisation" }, { "definitions": [ { "citation": [ "(Pariser, 2011, p. 9)" ], "text": "a unique universe of information for each of us" } ], "description": [ { "citation": [], "text": "the idea is that democratic society is at risk because personalised content and services limit the diversity of media content people are exposed to." } ], "examples": [ { "citation": [], "text": "a personalised news website could give more prominence to conservative media items, based on the inferred political interests of the user. When they form their political ideas, users of such personalised services may encounter fewer opinions or political arguments." } ], "related_terms": [ { "citation": [ "(Pariser, 2011)" ], "text": "pre-selected personalisation" }, { "citation": [], "text": "information cocoons" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "filter bubble" }, { "definitions": [ { "citation": [ "(Negroponte, 1995, p. 153)" ], "text": "This kind of newspaper is printed in an edition of one." } ], "description": [ { "citation": [ "Negroponte (1995)" ], "text": "people would soon be able to choose their own personalised media experiences" } ], "examples": [ { "citation": [ "(Negroponte, 1995, p. 153)" ], "text": "Imagine a future in which your interface agent can read every newswire and newspaper and catch every TV and radio broadcast on the planet, and then construct a personalized summary." } ], "related_terms": [ { "citation": [], "text": "self-selected personalisation" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "daily me" }, { "definitions": [ { "citation": [], "text": "situations in which people choose to encounter likeminded opinions exclusively." }, { "citation": [], "text": "where people actively choose which content they receive" } ], "description": [ { "citation": [], "text": "People tend to avoid information that challenges their point of view, for example by avoiding news outlets that often feature editorials that favour an opposing political camp." } ], "examples": [ { "citation": [], "text": "a person who opposes immigration might want to avoid information that specifies how much a country has gained due to immigration, while paying a lot of attention to news stories about problems related to immigration." }, { "citation": [], "text": "somebody might self-select personalisation by following people on Twitter who hold like-minded opinions." } ], "related_terms": [ { "citation": [ "(e.g. Stroud, 2011)" ], "text": "selective exposure" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "personalisation" } ], "synonyms": [ { "citation": [ "(Thurman & Schifferes 2012; see also Treiblmaier, Madlberger, Knotzer, & Pollach, 2004)" ], "text": "explicit personalisation" } ], "term": "self-selected personalisation" }, { "definitions": [ { "citation": [], "text": "personalisation driven by websites, advertisers, or other actors, often without the user's deliberate choice, input, knowledge or consent." }, { "citation": [], "text": "where algorithms personalise content for users without any deliberate user choice." } ], "description": [ { "citation": [], "text": "Pre-selected personalisation may be chosen by the user, or not." }, { "citation": [], "text": "pre-selected personalisation is not a result of a user's direct choice -but of a choice that is determined by algorithms." } ], "examples": [ { "citation": [], "text": "some people may realise that Facebook personalises the content in its newsfeed. If these people explicitly use Facebook to see the curated, pre-selected collection of news about 'friends', the newsfeed is an example of chosen pre-selected personalisation. Other people, however, may not realise that the newsfeed on Facebook is personalised; those people do not explicitly choose pre-selected personalisation." } ], "related_terms": [ { "citation": [ "(Pariser, 2011)" ], "text": "filter bubble" }, { "citation": [ "(Hildebrandt, 2010)" ], "text": "ambient intelligence" } ], "subtypes": [ { "citation": [], "text": "chosen pre-selected personalisation" } ], "supertypes": [ { "citation": [], "text": "personalisation" } ], "synonyms": [ { "citation": [ "(Thurman & Schifferes 2012; see also Treiblmaier, Madlberger, Knotzer, & Pollach, 2004)" ], "text": "implicit personalisation" } ], "term": "pre-selected personalisation" }, { "definitions": [ { "citation": [ "(Garret, 2009a, 2009b; Garret, Carnahan, & Lynch, 2011)" ], "text": "people select information they agree with" } ], "description": [ { "citation": [], "text": "Selectively using information that matches pre-existing beliefs is human." } ], "examples": [], "related_terms": [ { "citation": [ "(Garret, 2009a, 2009b; Garret, Carnahan, & Lynch, 2011)" ], "text": "selective avoidance" }, { "citation": [ "(e.g. Stroud, 2011)" ], "text": "self-selected personalisation" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "selective exposure" }, { "definitions": [ { "citation": [ "(Garret, 2009a, 2009b; Garret, Carnahan, & Lynch, 2011)" ], "text": "people actually avoid possibly conflicting information" } ], "description": [ { "citation": [ "(Festinger, 1957)" ], "text": "People tend to avoid media content that conflicts with their beliefs" } ], "examples": [], "related_terms": [ { "citation": [ "(Garret, 2009a, 2009b; Garret, Carnahan, & Lynch, 2011)" ], "text": "selective exposure" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "selective avoidance" }, { "definitions": [ { "citation": [ "(Sunstein 2006, p. 9)" ], "text": "communication universes in which we hear only what we choose and only what comforts us and pleases us" } ], "description": [ { "citation": [ "(Sunstein 2006, p. 9)" ], "text": "people locking themselves in 'information cocoons'" } ], "examples": [ { "citation": [], "text": "somebody might self-select personalisation by following people on Twitter who hold like-minded opinions." } ], "related_terms": [ { "citation": [], "text": "echo chambers" }, { "citation": [], "text": "self-selected personalisation" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "information cocoons" }, { "definitions": [ { "citation": [ "(Habermas, 1989)" ], "text": "societally relevant ideas are formulated, negotiated and distributed, and in the process the ruling authorities' actions are kept under control and guided" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "public sphere" }, { "definitions": [ { "citation": [ "(Lyon, 2003, p. 20)" ], "text": "obtain[ing] personal and group data in order to classify people and populations according to varying criteria, to determine who should be targeted for special treatment, suspicion, eligibility, inclusion, access, and so on" } ], "description": [ { "citation": [ "(Turow, 2011)" ], "text": "profiling and classification in one domain (for example in advertising) may outgrow its original context and define other domains of our life" }, { "citation": [ "(Turow, 2011, p. 196)" ], "text": "may further erode the tolerance and mutual dependence between diverse groups that enable a society to work" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Social sorting" } ] }, { "paper_id": "35266513e601aed2e2707e9263b2ccd466644b60", "split": "original_test", "metadata": { "title": "The Origins and Consequences of Affective Polarization in the United States", "authors": [ "S. Iyengar", "Y. Lelkes", "Matthew Levendusky", "Neil Malhotra", "S. Westwood" ], "publication_year": "2019", "doi": "10.1146/annurev-polisci-051117-073034", "venue": "Annual review of political science (Palo Alto, Calif. Print)" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "animosity between the parties" }, { "citation": [ "(Iyengar & Westwood 2015, p. 691)" ], "text": "the tendency of people identifying as Republicans or Democrats to view opposing partisans negatively and copartisans positively" }, { "citation": [], "text": "the difference between the score given to the party of the respondent and the score given to the opposing party" } ], "description": [ { "citation": [ "(Fiorina et al. 2005)" ], "text": "Our conceptualization of polarization as rooted in affect and identity stands in contrast to a long tradition in political science of studying polarization as the difference between the policy positions of Democrats and Republicans" }, { "citation": [ "(Iyengar et al. 2012, Mason 2015)" ], "text": "affective polarization is largely distinct from the ideological divide, and that extremity in issue opinions is not a necessary condition for affective polarization" } ], "examples": [ { "citation": [], "text": "Ordinary Americans increasingly dislike and distrust those from the other party." }, { "citation": [], "text": "Democrats and Republicans both say that the other party's members are hypocritical, selfish, and closed-minded, and they are unwilling to socialize across party lines, or even to partner with opponents in a variety of other activities." } ], "related_terms": [ { "citation": [], "text": "partisan animus" }, { "citation": [], "text": "partisan group identity" }, { "citation": [], "text": "ideological polarization" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "affective polarization" }, { "definitions": [ { "citation": [ "(Green et al. 2002, Huddy et al. 2015)" ], "text": "identifying with the Democrat group or the Republican group" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "social identity" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "partisanship" }, { "definitions": [ { "citation": [ "Tajfel & Turner 1979" ], "text": "our own party" } ], "description": [ { "citation": [ "Billig & Tajfel 1973" ], "text": "A vast literature in social psychology demonstrates that any such in-group/out-group distinction, even one based on the most trivial of shared characteristics, triggers both positive feelings for the in group and negative evaluations of the out group" } ], "examples": [], "related_terms": [ { "citation": [ "Tajfel & Turner 1979" ], "text": "out group" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "in group" }, { "definitions": [ { "citation": [ "Tajfel & Turner 1979" ], "text": "the opposing party" } ], "description": [ { "citation": [ "Billig & Tajfel 1973" ], "text": "A vast literature in social psychology demonstrates that any such in-group/out-group distinction, even one based on the most trivial of shared characteristics, triggers both positive feelings for the in group and negative evaluations of the out group" } ], "examples": [], "related_terms": [ { "citation": [ "Tajfel & Turner 1979" ], "text": "in group" } ], "subtypes": [], "supertypes": [], "synonyms": [ { "citation": [ "Tajfel & Turner 1979" ], "text": "out party" } ], "term": "out group" }, { "definitions": [ { "citation": [], "text": "the extent to which individuals feel comfortable interacting with out-group members in various settings." } ], "description": [ { "citation": [], "text": "If partisanship is an important social identity in its own right, partisans should be averse to entering into close interpersonal relations with their opponents." } ], "examples": [ { "citation": [ "Iyengar et al. (2012)" ], "text": "Americans have become increasingly averse to the prospect of their child marrying someone from the opposing party." } ], "related_terms": [ { "citation": [], "text": "partisan affect" }, { "citation": [], "text": "affective polarization" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "social distance" }, { "definitions": [ { "citation": [ "Iyengar & Westwood (2015)", "Carlin & Love (2013)" ], "text": "the difference between financial allocations to copartisans and opposing partisans." } ], "description": [ { "citation": [], "text": "copartisans consistently receive a bonus while opposing partisans are subject to a financial penalty." } ], "examples": [], "related_terms": [ { "citation": [], "text": "affective polarization" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "partisan bias" }, { "definitions": [ { "citation": [ "(Levendusky 2009)" ], "text": "partisans who identify with the party most closely reflecting their ideology" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "sorting" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "sorted partisans" }, { "definitions": [ { "citation": [], "text": "the alignment of ideology and partisanship" } ], "description": [ { "citation": [ "(Lelkes 2018, Mason 2018a)" ], "text": "sorting accounting for only about 5% of the variance in affective polarization" } ], "examples": [], "related_terms": [ { "citation": [], "text": "sorted partisans" }, { "citation": [], "text": "ideological polarization" }, { "citation": [], "text": "affective polarization" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "sorting" } ] }, { "paper_id": "3584741", "split": "original_test", "metadata": { "title": "A Survey on Event-Based News Narrative Extraction", "authors": [ "Brian Felipe Keith-Norambuena", "Tanushree Mitra", "Chris North" ], "publication_year": "2023", "doi": "10.1145/3584741", "venue": "ACM Computing Surveys" }, "definition_records": [ { "definitions": [ { "citation": [ "[42]" ], "text": "a coherent system of interrelated stories" }, { "citation": [], "text": "narratives are a systematic collection of interrelated stories with coherent themes." } ], "description": [ { "citation": [ "[75]" ], "text": "narratives as communication tools to construct a shared meaning of events with the purpose of influencing the behaviors" } ], "examples": [], "related_terms": [ { "citation": [], "text": "stories" }, { "citation": [], "text": "events" } ], "subtypes": [ { "citation": [], "text": "news narratives" }, { "citation": [], "text": "interactive narratives" } ], "supertypes": [ { "citation": [], "text": "system of stories" } ], "synonyms": [], "term": "narratives" }, { "definitions": [ { "citation": [ "[1]" ], "text": "the fundamental units of narrative action-they are either an act involving characters and entities or a happening where no entities are causally involved" } ], "description": [ { "citation": [], "text": "one is focused on the actions and happenings of the narrative" } ], "examples": [], "related_terms": [ { "citation": [], "text": "characters" }, { "citation": [], "text": "entities" }, { "citation": [], "text": "stories" } ], "subtypes": [ { "citation": [], "text": "events as sentences" }, { "citation": [], "text": "events as documents" }, { "citation": [], "text": "events as clusters" } ], "supertypes": [ { "citation": [], "text": "fundamental units of narrative action" } ], "synonyms": [], "term": "events" }, { "definitions": [ { "citation": [], "text": "computational narrative representations as an event structure that represents different stories." } ], "description": [ { "citation": [], "text": "these event structures are discrete in nature (e.g., a graph or a timeline of events)." }, { "citation": [], "text": "some of the extraction methods that we review will leverage entity-based information, but they are not the focus of their representation." } ], "examples": [], "related_terms": [ { "citation": [], "text": "event structure" }, { "citation": [], "text": "stories" } ], "subtypes": [ { "citation": [], "text": "linear structure" }, { "citation": [], "text": "event graph structures" } ], "supertypes": [ { "citation": [], "text": "narrative representation" } ], "synonyms": [], "term": "computational narrative representations" }, { "definitions": [ { "citation": [], "text": "Given a set of news articles, the news narrative extraction task generates a discrete structure comprised of events to represent the narrative." } ], "description": [ { "citation": [], "text": "the goal is to obtain a narrative representation from a set of articles rather than on document-level extraction" }, { "citation": [], "text": "the structure is left deliberately ambiguous to allow for different types of representations, such as event timelines or event graphs." } ], "examples": [], "related_terms": [ { "citation": [], "text": "narrative generation" }, { "citation": [], "text": "narrative forecasting" }, { "citation": [], "text": "narrative analysis" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "natural language processing" } ], "synonyms": [ { "citation": [], "text": "(event-based) narrative extraction task" } ], "term": "News Narrative Extraction" }, { "definitions": [ { "citation": [ "[35,36]" ], "text": "Narrative generation is a fundamentally different task from extraction that seeks to create new fictional narratives rather than extract a narrative that already exists (either fictional or nonfictional)" } ], "description": [ { "citation": [], "text": "the focus of narrative generation is usually fictional narratives, not news narratives." } ], "examples": [], "related_terms": [ { "citation": [], "text": "narrative extraction" }, { "citation": [], "text": "narrative forecasting" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "task" } ], "synonyms": [], "term": "narrative generation" }, { "definitions": [ { "citation": [ "[131]" ], "text": "Narrative forecasting (i.e., predicting the next events in the narrative) is a task that lies between extraction and generation, but its focus is on generating new events rather than on extracting the complete narrative" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "extraction" }, { "citation": [], "text": "generation" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "task" } ], "synonyms": [], "term": "Narrative forecasting" }, { "definitions": [ { "citation": [ "[79,95]" ], "text": "Narrative analysis methods use existing extraction approaches to obtain a computational representation of the narrative and then use it to analyze the narrative" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "extraction approaches" }, { "citation": [], "text": "computational representation" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "methods" } ], "synonyms": [], "term": "Narrative analysis" }, { "definitions": [ { "citation": [ "[19]" ], "text": "interactive narratives, as these are a fundamentally different type of narratives where the story can be changed through user feedback and actions" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "user feedback" }, { "citation": [], "text": "actions" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "narratives" } ], "synonyms": [], "term": "interactive narratives" }, { "definitions": [ { "citation": [], "text": "Event resolution refers to the abstraction level at which the events are extracted." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "event representation" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "abstraction level" } ], "synonyms": [], "term": "event resolution" }, { "definitions": [ { "citation": [], "text": "Events may be represented by relevant sentences extracted from a news article, and usually a single sentence is used for these purposes." } ], "description": [ { "citation": [], "text": "Sentence-level works represent events as either a single sentence (e.g., the most important sentence or a headline) or a set of sentences (e.g., a sample of representative sentences)." } ], "examples": [], "related_terms": [], "subtypes": [ { "citation": [], "text": "query-based approaches" }, { "citation": [], "text": "pre-filtered approaches" } ], "supertypes": [ { "citation": [], "text": "event resolution" } ], "synonyms": [ { "citation": [], "text": "events as sentences" } ], "term": "sentence-level resolution" }, { "definitions": [ { "citation": [], "text": "Events may also be represented by an entire document (i.e., a news article)." } ], "description": [ { "citation": [], "text": "Document-level works represent events directly as a single document (e.g., a full news article)." } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "event resolution" } ], "synonyms": [ { "citation": [], "text": "events as documents" } ], "term": "document-level resolution" }, { "definitions": [ { "citation": [], "text": "events may also be represented as sets of documents that refer to the same main event." } ], "description": [ { "citation": [], "text": "Cluster-level works represent events as sets of documents (e.g., multiple news articles that talk about the same basic event)." } ], "examples": [], "related_terms": [], "subtypes": [ { "citation": [], "text": "event threading" }, { "citation": [], "text": "event evolution" } ], "supertypes": [ { "citation": [], "text": "event resolution" } ], "synonyms": [ { "citation": [], "text": "events as clusters" } ], "term": "cluster-level resolution" }, { "definitions": [ { "citation": [], "text": "the simplest way to computationally represent a narrative is through a linear structure representing sequences of events (i.e., a timeline)." } ], "description": [ { "citation": [], "text": "Using a linear structure provides a simple approach to represent a narrative with a single storyline, but it does not appropriately model the nuances of narratives with multiple stories." } ], "examples": [], "related_terms": [ { "citation": [], "text": "graphbased structures" }, { "citation": [], "text": "single storyline" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "Structure" } ], "synonyms": [ { "citation": [], "text": "timeline" } ], "term": "linear structure" }, { "definitions": [ { "citation": [], "text": "The informing value depends on whether the headline provides factual information or an opinion, review, or another non-informing category." } ], "description": [ { "citation": [ "[128]" ], "text": "It is a binary value computed using a supervised learning approach based on an SVM classifier to separate facts from opinion" } ], "examples": [], "related_terms": [ { "citation": [], "text": "factual information" }, { "citation": [], "text": "opinion" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "metrics" } ], "synonyms": [], "term": "informing value" }, { "definitions": [ { "citation": [], "text": "Influence tries to measure the impact of an event on future events" } ], "description": [ { "citation": [], "text": "based on references from future events using similarity between future news articles and the headline of the event." } ], "examples": [ { "citation": [], "text": "\"the president resigns\" would lead to a \"new election\" event" } ], "related_terms": [ { "citation": [], "text": "future events" }, { "citation": [], "text": "references" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "metrics" } ], "synonyms": [], "term": "Influence" }, { "definitions": [ { "citation": [], "text": "the probability of a headline being duplicated." } ], "description": [ { "citation": [], "text": "a relevant event will be reported in multiple news outlets-that is, its reporting will be spread over multiple headlines." } ], "examples": [], "related_terms": [ { "citation": [], "text": "positive redundancy" }, { "citation": [], "text": "headlines" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "metrics" } ], "synonyms": [ { "citation": [], "text": "measure of positive redundancy" } ], "term": "Spread" }, { "definitions": [ { "citation": [ "[22]" ], "text": "a model that tracks the life cycle of events using an energy function, which increases when an event becomes popular and diminishes with time." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "life cycle of events" }, { "citation": [], "text": "energy function" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "model" } ], "synonyms": [], "term": "Aging theory" }, { "definitions": [ { "citation": [], "text": "Another approach to extracting narratives is based on modeling content similarity between events." } ], "description": [ { "citation": [], "text": "The exact choice of approach is highly dependent on the event representation." } ], "examples": [], "related_terms": [ { "citation": [], "text": "surface-level similarity comparisons" }, { "citation": [], "text": "topic similarity" }, { "citation": [], "text": "entity-based comparisons" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "extraction criteria" } ], "synonyms": [], "term": "Content Similarity" }, { "definitions": [ { "citation": [], "text": "Coherence metrics evaluate whether the narrative makes sense." } ], "description": [ { "citation": [], "text": "the geometric mean of the content similarity of events, using cosine or angular similarity, and their topical similarity, based on JS similarity of their topic distributions based on clustering." }, { "citation": [], "text": "Coherence measures the smoothness of a storyline, and a coherent story should not have drastic changes in content or topic." }, { "citation": [], "text": "coherence is not used 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[], "examples": [], "related_terms": [], "subtypes": [ { "citation": [], "text": "Coverage" }, { "citation": [], "text": "redundancy" }, { "citation": [], "text": "diversity" } ], "supertypes": [ { "citation": [], "text": "extraction metric" } ], "synonyms": [], "term": "Coverage-like metrics" }, { "definitions": [ { "citation": [], "text": "events should not be covered more than necessary, thus high redundancy can lead to coverage problems." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "diversity" }, { "citation": [], "text": "coverage" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "Coverage-like metrics" } ], "synonyms": [], "term": "redundancy" }, { "definitions": [ { "citation": [], "text": "Connectivity is simply the number of storylines that intersect." } ], "description": [ { "citation": [], "text": "narrative graphs avoid isolated stories, as they should be interwoven throughout the narrative." } ], "examples": [], "related_terms": [ { "citation": [], "text": "storylines" }, { "citation": [], "text": "narrative graphs" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "Structural Information" } ], "synonyms": [], "term": "connectivity" }, { "definitions": [ { "citation": [], "text": "differentia words are built from the set difference between the articles (in temporal order) and represent new knowledge in the story." } ], "description": [ { "citation": [], "text": "differentia words are more important when trying to find coherent sequences of articles." } ], "examples": [], "related_terms": [ { "citation": [], "text": "genus words" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "concepts" } ], "synonyms": [], "term": "differentia words" }, { "definitions": [ { "citation": [], "text": "whether this connection is based on the articles referring to the same news event, same-event connection" } ], "description": [ { "citation": [], "text": "the transitive nature of the 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[], "supertypes": [ { "citation": [], "text": "continuations" } ], "synonyms": [], "term": "reaction" }, { "definitions": [ { "citation": [], "text": "document similarity is defined by content similarity (e.g., cosine similarity) and a negative exponential penalty for temporally distant documents." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "content similarity" }, { "citation": [], "text": "temporally distant documents" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "similarity" } ], "synonyms": [], "term": "document similarity" }, { "definitions": [ { "citation": [], "text": "Most of the works that rely on user evaluations use subjective measures (i.e., user perception metrics)." } ], "description": [ { "citation": [ "[47,51,101]" ], "text": "These subjective metrics include concepts from usability, including criteria such as user preference" } ], "examples": [], "related_terms": [ { "citation": [], "text": "Task-Oriented 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Gelman" ], "publication_year": "2008", "doi": "10.1086/590649", "venue": "American Journal of Sociology" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "a process of alignment along multiple lines of potential disagreement and measured as growing constraint in individuals' preferences." } ], "description": [ { "citation": [], "text": "if people aligned along multiple, potentially divisive issues, even if they did not take extreme positions on each of them, the end result would be a polarized society." }, { "citation": [], "text": "issue alignment is more likely to amplify the ideological distance between citizens and thus increase public opinion polarization" } ], "examples": [], "related_terms": [ { "citation": [], "text": "political polarization" }, { "citation": [], "text": "opinion radicalization" }, { "citation": [], "text": "issue alignment" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Public opinion polarization" }, { "definitions": [ { "citation": [], "text": "polarization has to be conceived not only as a phenomenon of opinion radicalization, but also as a process of ideological division and preference alignment." } ], "description": [ { "citation": [], "text": "Political polarization constitutes a threat to the extent that it induces alignment along multiple lines of potential conflict and organizes individuals and groups around exclusive identities, thus crystallizing the public arena into opposite factions." } ], "examples": [], "related_terms": [ { "citation": [], "text": "Public opinion polarization" }, { "citation": [], "text": "opinion radicalization" }, { "citation": [], "text": "preference alignment" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "political polarization" }, { "definitions": [ { "citation": [], "text": "the variation of responses on an individual issue in the population, where more variation corresponds to more people on the extremes and fewer in the middle" } ], "description": [ { "citation": [], "text": "opinion alignment, rather than opinion radicalization, is the aspect of polarization that is more likely to have consequences on social integration and political stability." } ], "examples": [], "related_terms": [ { "citation": [], "text": "Public opinion polarization" }, { "citation": [], "text": "issue alignment" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "opinion radicalization" }, { "definitions": [ { "citation": [], "text": "the correlation of issue attitudes with party identification" }, { "citation": [], "text": "bivariate correlations of issues with party identification or ideology" }, { "citation": [], "text": "the relation between issues and ideology" } ], "description": [ { "citation": [], "text": "Increased issue partisanship can be thought of as a reflection of parties' differentiation and elite polarization" } ], "examples": [], "related_terms": [ { "citation": [], "text": "issue alignment" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "issue partisanship" }, { "definitions": [ { "citation": [], "text": "the correlation between pairs of issues" }, { "citation": [], "text": "the level of constraint within and between diverse issue domains" }, { "citation": [ "Converse (1964)" ], "text": "the extent to which such opinions are correlated with each other" } ], "description": [ { "citation": [ "Converse's (1964)" ], "text": "we use the term issue alignment instead of constraint, which is most common, because we focus on alignment between issue domains" }, { "citation": [], "text": "higher levels of issue alignment would suggest that citizens are increasingly splitting along multiple lines of potential conflict." } ], "examples": [ { "citation": [], "text": "If opinions are independent (thus, dimensions are orthogonal), 25% of people will prefer green circle, 25% green triangle, 25% yellow circle, and 25% yellow triangle. At the other extreme, if the two dimensions are perfectly correlated, 50% of the people will have one preference (e.g., green circle) and 50% will be in the opposite corner (yellow triangle), but the opinion distribution on the single issues will not change." } ], "related_terms": [ { "citation": [], "text": "issue partisanship" }, { "citation": [], "text": "opinion radicalization" }, { "citation": [], "text": "Public opinion polarization" } ], "subtypes": [], "supertypes": [], "synonyms": [ { "citation": [ "Converse's (1964)" ], "text": "constraint" } ], "term": "issue alignment" }, { "definitions": [ { "citation": [ "DiMaggio et al. (1996)" ], "text": "the level of opinion disagreement between subgroups" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "Public opinion polarization" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "intergroup polarization" }, { "definitions": [ { "citation": [], "text": "since the parties are now more clearly divided-and on a broader set of issues-it is easier for people to split accordingly, without changing their own views" } ], "description": [ { "citation": [], "text": "changes in the electorate should be interpreted as an illusory adjustment of citizens to the renovated partisanship of the political elite." } ], "examples": [], "related_terms": [ { "citation": [], "text": "public opinion polarization" }, { "citation": [], "text": "elite polarization" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "illusory adjustment" } ] }, { "paper_id": "3a03068318afdaa75a9dbdcbf960d63bf8035f0e", "split": "train", "metadata": { "title": "Local Does as Local Is: Information Content of the Geography of Individual Investors' Common Stock Investments", "authors": [ "Scott J. Weisbenner", "Z. Ivkovich" ], "publication_year": "2003", "doi": "10.2139/ssrn.359980", "venue": "" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "disproportionate preference for local stocks" } ], "description": [ { "citation": [], "text": "individual investors exhibit local bias" } ], "examples": [], "related_terms": [ { "citation": [], "text": "home bias" }, { "citation": [], "text": "local investments" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "local bias" } ] }, { "paper_id": "3b50e1808471dd5a8d19a50ef227b03774b80cae", "split": "dev", "metadata": { "title": "Transport and social exclusion: investigating the possibility of promoting inclusion through virtual mobility", "authors": [ "Susan B. Kenyon", "G. Lyons", "J. Rafferty" ], "publication_year": "2002", "doi": "10.1016/s0966-6923(02)00012-1", "venue": "" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "The unique interplay of a number of factors, whose consequence is the denial of access, to an individual or group, to the opportunity to participate in the social and political life of the community, resulting not only in diminished material and non-material quality of life, but also in tempered life chances, choices and reduced citizenship." } ], "description": [ { "citation": [ "(Duffy, 1998)" ], "text": "social exclusion centres upon the processes of unequal access to participation in society" }, { "citation": [ "(Dibben, 2001;Judge, 1995;Room, 1995)" ], "text": "social exclusion is relational, with a focus upon resource and power relationships between individuals, groups and the state" }, { "citation": [], "text": "It is a heterogeneous concept, with interrelated causes and components which can, however, be experienced independently of each other and at different times, to different extents, by different individuals and groups." }, { "citation": [ "(Duffy, 1998;Walker and Walker, 1997)" ], "text": "This definition, in highlighting the denial of access to opportunity, places emphasis upon structural constraints to participation, removing the individual culpability that is implied by definitions suggesting an inability to participate in society" }, { "citation": [ "(Bhalla and Lapeyre, 1997;Foley, 1999;PAT 18, nd)" ], "text": "Exclusion should not, therefore, be seen as a single, additive quality, in which characteristics are necessarily related, the sum of which is greater than each individual part" }, { "citation": [ "(Oppenheim, 1998)" ], "text": "In addition, many of the characteristics of exclusion are non-quantifiable (Oppenheim, 1998), for example, powerlessness, self-esteem, isolation and perceptions of choice." } ], "examples": [], "related_terms": [ { "citation": [], "text": "poverty" }, { "citation": [], "text": "self-exclusion" }, { "citation": [], "text": "mobility-related exclusion" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "social exclusion" }, { "definitions": [ { "citation": [], "text": "a gap in access to ICTs that is determined by an individual's characteristics" } ], "description": [ { "citation": [ "(Graham and Marvin, 1999, PAT 15, 2000)" ], "text": "people who experience social exclusion are highly likely to also be excluded from access to the Internet and that, without access to the Internet, disadvantage and exclusion will be further reinforced" } ], "examples": [], "related_terms": [ { "citation": [], "text": "social exclusion" }, { "citation": [], "text": "Virtual mobility" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "digital divide" } ] }, { "paper_id": "3dffde1e26f12b0f30abe8b5a046932fa6004ae0", "split": "dev", "metadata": { "title": "Fake News or Truth? Using Satirical Cues to Detect Potentially Misleading News", "authors": [ "Victoria L. Rubin", "Niall Conroy", "Yimin Chen", "Sarah Cornwell" ], "publication_year": "2016", "doi": "10.18653/v1/w16-0802", "venue": "" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "a type of deception that intentionally incorporates cues revealing its own deceptiveness" }, { "citation": [ "(Phiddian, 2013)" ], "text": "a rhetorical strategy (in any medium) that seeks wittily to provoke an emotional and intellectual reaction in an audience on a matter of public … significance" }, { "citation": [], "text": "a type of deception, but one that is intended to be found out by at least some subset of the audience" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "deception" } ], "synonyms": [], "term": "Satire" }, { "definitions": [ { "citation": [], "text": "a genre of satire that mimics the format and style of journalistic reporting" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "satire" } ], "synonyms": [], "term": "News satire" }, { "definitions": [ { "citation": [ "(Tsur, Davidov, & Rappoport, 2010)" ], "text": "verbal irony … the activity of saying or writing the opposite of what you mean" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [ { "citation": [], "text": "verbal irony" } ], "term": "Sarcasm" } ] }, { "paper_id": "3fbb00b939c3e84989ed922a6366608d1155aeb3", "split": "train", "metadata": { "title": "Stigma, prejudice, discrimination and health ☆", "authors": [ "J. Stuber", "I. Meyer", "Bruce G. 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Gummadi" ], "publication_year": "2016", "doi": "10.1145/3038912.3052660", "venue": "The Web Conference" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "there is disparate impact when the decision outcomes disproportionately benefit or hurt members of certain sensitive attribute value groups." } ], "description": [ { "citation": [], "text": "disparate impact arises when a decision making system provides outputs that benefit (hurt) a group of people sharing a value of sensitive attribute more frequently than other groups of people." } ], "examples": [], "related_terms": [ { "citation": [], "text": "disparate treatment" }, { "citation": [], "text": "disparate mistreatment" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "disparate impact" }, { "definitions": [ { "citation": [], "text": "a decision making process to be suffering from disparate mistreatment with respect to a given sensitive attribute (e.g., race) if the misclassification rates differ for groups of people having different values of that sensitive attribute (e.g., blacks and whites)." } ], "description": [ { "citation": [], "text": "Intuitively, disparate mistreatment can arise in any automated decision making system whose outputs (or decisions) are not perfectly (i.e., 100%) accurate." } ], "examples": [], "related_terms": [ { "citation": [], "text": "disparate treatment" }, { "citation": [], "text": "disparate impact" }, { "citation": [], "text": "false discovery" }, { "citation": [], "text": "false omission" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "disparate mistreatment" }, { "definitions": [ { "citation": [], "text": "there is disparate treatment when the decisions an individual user receives change with changes to her sensitive attribute information" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "disparate impact" }, { "citation": [], "text": "disparate mistreatment" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "disparate treatment" } ] }, { "paper_id": "641b12df54a3d853bad273bf5fed2c0965936f83", "split": "dev", "metadata": { "title": "Discrimination in a Low-Wage Labor Market: A Field Experiment", "authors": [ "D. 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All three of us went over.… She looked at me and told me she 'needed to speak to these two' and that I could go back.\" Zuri returned to the bus stop, while his white and Latino test partners were both asked to come back at 5 p.m. that day to start work." } ], "related_terms": [ { "citation": [], "text": "shifting standards" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "categorical exclusion" } ] }, { "paper_id": "6924de9691e8f1bb5477da3907e2f5372ad0e565", "split": "new_test", "metadata": { "title": "Social Media, Political Polarization, and Political Disinformation: A Review of the Scientific Literature", "authors": [ "Joshua A. Tucker", "A. Guess", "Pablo Barberá", "Cristian Vaccari", "A. Siegel", "Sergey Sanovich", "D. Stukal", "B. 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Bush for the query \"miserable failure.\"" }, { "citation": [], "text": "similar or identical posts pointing to specific websites" } ], "related_terms": [ { "citation": [], "text": "keyword stuffing" }, { "citation": [], "text": "mutual admiration societies" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "Traditional spamming tactics" } ], "synonyms": [], "term": "link bombs" }, { "definitions": [ { "citation": [], "text": "false information that may be unintentionally propagated" }, { "citation": [], "text": "unwittingly false information" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "misinformation" }, { "definitions": [ { "citation": [], "text": "potentially factually correct information, but packaged in a way so as to disparage opposing viewpoints (i.e., the point is not so much to present information as it is to rally public support)" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "online propaganda" }, { "definitions": [ { "citation": [], "text": "unverified and instrumentally relevant information statements in circulation that arise in contexts of ambiguity, danger, or potential threat and that function to help people make sense and manage risk" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [ { "citation": [], "text": "conspiracy rumors" } ], "supertypes": [], "synonyms": [], "term": "rumors" }, { "definitions": [ { "citation": [], "text": "removing some content from online platforms, while leaving other forms content alone" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "manipulation of search rankings" }, { "citation": [], "text": "hacking and releasing" }, { "citation": [], "text": "directly sharing disinformation on social media platforms" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "Tactics for Spreading Disinformation" } ], "synonyms": [], "term": "selective censorship" }, { "definitions": [ { "citation": [], "text": "(1) Human accounts that post politically motivated, generally pro-government content, often for a fee, or (2) human accounts that post provocative (generally \"anti-PC\") content, often with graphic language and misogynistic content, either out of political conviction or simply for the \"thrill\" of doing so." }, { "citation": [], "text": "people who intentionally bait others in order to elicit an emotional response." } ], "description": [ { "citation": [], "text": "categories of actors that can play important roles in manipulating search rankings, sharing hacked information, and directly introducing and sharing disinformation on social media platforms" }, { "citation": [ "(Phillips 2015)" ], "text": "Trolls post inflammatory messages to sow discord and cause reactions (Phillips 2015)." } ], "examples": [ { "citation": [], "text": "trolls from the infamous Russian \"troll factory\" Internet Research Agency" } ], "related_terms": [ { "citation": [], "text": "bots" } ], "subtypes": [ { "citation": [], "text": "independent trolls" }, { "citation": [], "text": "paid political trolls" } ], "supertypes": [], "synonyms": [], "term": "Trolls" }, { "definitions": [ { "citation": [], "text": "When the name of another Twitter user is contained in a tweet." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "Twitter: retweets" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Twitter: mentions" }, { "definitions": [ { "citation": [], "text": "When one user shares the tweet of another user." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "Twitter: mentions" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Twitter: retweets" }, { "definitions": [ { "citation": [], "text": "A \"tweet\" refers to a post on Twitter; previously limited to 140 characters, recently expanded to 280 characters." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [ { "citation": [], "text": "tweet" } ], "term": "Twitter: tweets" }, { "definitions": [ { "citation": [], "text": "growth in the diffusion of a message through person-to-person contacts similar to the spread of a disease" } ], "description": [ { "citation": [ "(Goel et al. 2015)" ], "text": "the \"viral\" model, where messages achieve mass diffusion via large numbers of individual peer-to-peer transmissions" } ], "examples": [], "related_terms": [ { "citation": [], "text": "informational cascades" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "virality" } ] }, { "paper_id": "6b7fb77e515e432fc12cf7779c796aa98e18c68d", "split": "train", "metadata": { "title": "Talking about Poverty: News Framing of Who is Responsible for Causing and Fixing the Problem", "authors": [ "Sei-Hill Kim", "John P. 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}, { "definitions": [ { "citation": [ "[231]" ], "text": "the general observation that members of opposing groups rate a news article as biased against their point of view" }, { "citation": [ "[101,181,231]" ], "text": "people perceive media coverage as biased against their side, regardless of the actual political position of the article" } ], "description": [ { "citation": [], "text": "a cognitive bias rather than a characteristic of the media landscape" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "cognitive bias" } ], "synonyms": [ { "citation": [], "text": "HMP" } ], "term": "hostile media phenomenon" }, { "definitions": [ { "citation": [], "text": "how media discourse is structured into interpretive packages that give meaning to an issue" } ], "description": [ { "citation": [ "[53,65]" ], "text": "subsumes biases resulting from how events and entities are framed in a text" } ], "examples": [], "related_terms": [ { "citation": 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"gender bias" }, { "citation": [], "text": "racial bias" }, { "citation": [], "text": "religion bias" } ], "supertypes": [], "synonyms": [], "term": "group bias" }, { "definitions": [ { "citation": [ "[43]" ], "text": "characterized by the dominance of one gender over others in any medium" } ], "description": [ { "citation": [ "[43,183]" ], "text": "resulting in the under-representation of the less dominant gender and the formation of stereotypes" } ], "examples": [], "related_terms": [ { "citation": [ "[10,116]" ], "text": "selection bias" }, { "citation": [ "[32,135]" ], "text": "coverage bias" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "group bias" } ], "synonyms": [], "term": "Gender Bias" }, { "definitions": [ { "citation": [ "[39]", "[39,161]" ], "text": "Racial bias refers to the systematic disproportionate representation of ethical groups, often minorities, in a specific context." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "group bias" } ], "synonyms": [], "term": "Racial bias" }, { "definitions": [ { "citation": [ "[64]" ], "text": "examining text for its emotional content or polarity" } ], "description": [ { "citation": [ "[97,109]" ], "text": "can detect biases in statements or articles" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Sentiment Analysis" }, { "definitions": [ { "citation": [ "[122]" ], "text": "non-neutral news reporting" } ], "description": [ { "citation": [], "text": "can be described as a combination of linguistic and text-level biases on a document level" } ], "examples": [], "related_terms": [ { "citation": [], "text": "linguistic bias" }, { "citation": [], "text": "text-level context bias" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Hyperpartisanship" }, { "definitions": [ { "citation": [], "text": "quantify words and n-grams in the text to analyze bias" } ], 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[], "related_terms": [ { "citation": [ "[121,198]" ], "text": "in-group favoritism" }, { "citation": [ "[121,198]" ], "text": "out-group derogation" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "social identity and categorization theory" }, { "definitions": [ { "citation": [], "text": "explains moral differences across cultures" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Moral foundation theory" }, { "definitions": [ { "citation": [], "text": "identifies linguistic biases to identify the political biases" } ], "description": [ { "citation": [], "text": "an umbrella term closely related to partisan bias" } ], "examples": [], "related_terms": [ { "citation": [], "text": "partisan bias" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Political Stance Detection" } ] }, { "paper_id": "https://link.springer.com/article/10.1007/s00799-018-0261-y", "split": "train", "metadata": { "title": "Automated identification of media bias in news articles: an interdisciplinary literature review", "authors": [ "Felix Hamborg", "K. Donnay", "Bela Gipp" ], "publication_year": "2018", "doi": "10.1007/s00799-018-0261-y", "venue": "International Journal on Digital Libraries" }, "definition_records": [ { "definitions": [ { "citation": [ "[85]" ], "text": "describe the main event of a news article, i.e., who did what, when, where, and why" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "5Ws" }, { "definitions": [ { "citation": [ "[152]" ], "text": "aims to find the emotions that a text induces on the contained concepts, e.g., entities or activities, by comparing relevant words from the text, e.g., nearby the investigated concept, with affect dictionaries" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "sentiment analysis" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Affect analysis" }, { "definitions": [ { "citation": [], "text": "the ability of news publishers to influence which topics are 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[], "related_terms": [ { "citation": [], "text": "frames" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "framing" }, { "definitions": [ { "citation": [], "text": "relates to which stories media outlets select or reject for reporting" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [ "[34]" ], "text": "media bias" } ], "synonyms": [ { "citation": [], "text": "selection bias" }, { "citation": [], "text": "agenda bias" } ], "term": "Gatekeeping bias" }, { "definitions": [ { "citation": [], "text": "present if an outlet biases articles to promote a specific opinion on a topic" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [ "[33]" ], "text": "media bias" } ], "synonyms": [], "term": "Ideological bias" }, { "definitions": [ { "citation": [ "[13]" ], "text": "journalists and other involved parties implement purposely to achieve a specific goal" } ], 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"text": "word choice" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "labeling and word choice" }, { "definitions": [ { "citation": [], "text": "slanted news coverage" }, { "citation": [ "[30]" ], "text": "must both be intentional, i.e., reflect a conscious act or choice, and it must be sustained, i.e., represent a systematic tendency rather than an isolated incident" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [ { "citation": [ "[33]" ], "text": "ideology" }, { "citation": [ "[33]" ], "text": "spin" }, { "citation": [ "[34]" ], "text": "coverage" }, { "citation": [ "[34]" ], "text": "gatekeeping" }, { "citation": [ "[34]" ], "text": "statement" } ], "supertypes": [], "synonyms": [], "term": "Media bias" }, { "definitions": [ { "citation": [], "text": "one of the most popular approaches to enable users to get an overview of the large amounts of news that is published nowadays" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "news aggregation pipeline" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "News aggregation" }, { "definitions": [ { "citation": [], "text": "aims to find the most important news topics, and present them in a compressed form to users" } ], "description": [ { "citation": [ "[116,117]" ], "text": "Data gathering, i.e., crawling articles from news websites" }, { "citation": [ "[116,117]" ], "text": "Article extraction from website data, which is typically HTML or RSS" }, { "citation": [ "[116,117]" ], "text": "Grouping, i.e., finding and grouping related articles reporting on the same topic or event" }, { "citation": [ "[116,117]" ], "text": "Summarization of related articles" }, { "citation": [ "[116,117]" ], "text": "Visualization, e.g., presenting the most important topics to users" } ], "examples": [], "related_terms": [ { "citation": [], "text": "News aggregation" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "news aggregation pipeline" }, { "definitions": [ { "citation": [], "text": "placing the picture in context using a caption" } ], "description": [ { "citation": [], "text": "Captions below images and referrals to the images in the main text provide images with the needed textual context" } ], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "picture explanation" }, { "definitions": [ { "citation": [ "[6,34]" ], "text": "The placement and size allocation of a story indicates the value a news outlet assigns to that story" } ], "description": [], "examples": [ { "citation": [], "text": "the size and the number of columns of articles present in newspapers, or the broadcast length in minutes dedicated to a specific topic" } ], "related_terms": [ { "citation": [], "text": "frame analysis" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "placement and size allocation" }, { "definitions": [ { "citation": [], "text": "how news consumers tend to evaluate a topic is influenced by their (prior) perception of the specific issues that were portrayed in news on that topic" } ], "description": [], "examples": [], "related_terms": [ { "citation": [ "[35]", "[53]" ], "text": "agenda setting" }, { "citation": [ "[35]", "[53]" ], "text": "framing" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Priming theory" }, { "definitions": [ { "citation": [ "[143]" ], "text": "aims to extract an author's attitude toward a semantic concept mentioned in the text" } ], "description": [ { "citation": [ "[143]" ], "text": "Current sentiment analysis methods reliably extract the unambiguously stated sentiment" } ], "examples": [ { "citation": [ "[143]" ], "text": "identify whether customers used \"positive,\" such as \"good\" and \"durable,\" or \"negative\" words, such as \"poor quality,\" to review a product" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "sentiment analysis" }, { "definitions": [ { "citation": [], "text": "Journalists must decide on the trustworthiness of information sources and the actuality of information for a selected event" } ], "description": [ { "citation": [], "text": "may lead to biased coverage, e.g., if journalists mainly consult sources supporting one perspective when writing the article" } ], "examples": [], "related_terms": [ { "citation": [], "text": "source selection bias" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "source selection" }, { "definitions": [ { "citation": [], "text": "refers to the overall perception of an article" } ], "description": [ { "citation": [], "text": "includes other factors, such as the order of information presented in a news article, the article's tone, and emphasis on certain facts" }, { "citation": [], "text": "concerned with the context of presented information" } ], "examples": [], "related_terms": [ { "citation": [], "text": "media bias" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Spin" }, { "definitions": [ { "citation": [], "text": "present if the outlet attempts to create a memorable story" }, { "citation": [], "text": "a form of media bias that represents the overall bias of a news article" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [ "[33]" ], "text": "media bias" } ], "synonyms": [], "term": "Spin bias" }, { "definitions": [ { "citation": [], "text": "concerned with how articles choose to report on concepts" } ], "description": [], "examples": [ { "citation": [ "[35]" ], "text": "For example, in the US elections, a well-observed bias arises from editorial slant [35], in which the editorial position on a given presidential candidate affects the quantity and tone of a newspaper's coverage." } ], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [ "[34]" ], "text": "media bias" } ], "synonyms": [ { "citation": [], "text": "presentation bias" } ], "term": "Statement bias" }, { "definitions": [ { "citation": [], "text": "how the article refers to an entity" } ], "description": [], "examples": [ { "citation": [], "text": "\"coalition forces\" versus \"invading forces\"" } ], "related_terms": [ { "citation": [], "text": "labeling" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "word choice" } ] }, { "paper_id": "https://media-bias-research.org/wp-content/uploads/2024/07/Preprint_ICWSM_25_NewsUnfold", "split": "original_test", "metadata": { "title": "NewsUnfold: Creating a News-Reading Application That Indicates Linguistic Media Bias and Collects Feedback", "authors": [ "Smi Hinterreiter", "Martin Wessel", "Fabian Schliski", "Isao Echizen", "Marc Erich Latoschik", "Timo Spinde" ], "publication_year": "2024", "doi": "", "venue": "Proceedings of the ACM on Human-Computer Interaction (preprint)" }, "definition_records": [ { "definitions": [ { "citation": [ "(Spinde et al. 2024)" ], "text": "a bias by word choice to transmit a perspective that 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"https://www.sciencedirect.com/science/article/pii/S0957417423021437", "split": "original_test", "metadata": { "title": "A systematic review on media bias detection: What is media bias, how it is expressed, and how to detect it", "authors": [ "Francisco-Javier Rodrigo-Ginés", "Jorge Carrillo-de-Albornoz", "Laura Plaza" ], "publication_year": "2023", "doi": "10.1016/j.eswa.2023.121641", "venue": "Expert systems with applications" }, "definition_records": [ { "definitions": [ { "citation": [ "(Yap, 2013)" ], "text": "The Ad Hominem bias is when a journalist attacks another person instead of their argument" } ], "description": [ { "citation": [], "text": "Such attacks divert attention away from the substantive issues and focus it on personal characteristics or actions, potentially leading the public to form opinions based on character assaults rather than policy strengths or weaknesses." } ], "examples": [], "related_terms": [ { "citation": [ "(Yap, 2013)" ], "text": "mudslinging bias" }, { "citation": [], "text": "argument" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Ad Hominem bias" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "Appealing to an authority figure instead of using logic." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "authority figure" }, { "citation": [], "text": "logic" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [ { "citation": [], "text": "Ad verecundiam" } ], "term": "Appeal to authority" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "Consists in appealing to the fact that everyone else is doing it or everyone else believes it." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "groupthink" }, { "citation": [], "text": "evidence" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [ { "citation": [], "text": "Ad populum" } ], "term": "Appeal to groupthink" }, { "definitions": [ { "citation": [], "text": "a situation in which you support or oppose someone or something in an unfair way because you are influenced by your personal opinions" }, { "citation": [], "text": "an unfair preference for one thing" } ], "description": [ { "citation": [], "text": "Bias in media is multi-faceted and deeply contextual." } ], "examples": [], "related_terms": [ { "citation": [], "text": "opinion" } ], "subtypes": [ { "citation": [], "text": "media bias" } ], "supertypes": [ { "citation": [], "text": "situation" }, { "citation": [], "text": "preference" } ], "synonyms": [], "term": "bias" }, { "definitions": [ { "citation": [ "(Hamborg, 2020)" ], "text": "Labeling and word choice are biases related to how the journalist choose the words to present the story" } ], "description": [ { "citation": [], "text": "the journalist may use loaded language to make one side seem more favorable." } ], "examples": [ { "citation": [ "(Parker-Bass et al., 2022)" ], "text": "''coalition forces''" }, { "citation": [ "(Parker-Bass et al., 2022)" ], "text": "''invading forces''" } ], "related_terms": [ { "citation": [], "text": "Labeling" }, { "citation": [], "text": "word choice" }, { "citation": [], "text": "loaded language" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Hamborg, 2020)" ], "text": "biases" } ], "synonyms": [], "term": "Bias by labeling and word choice" }, { "definitions": [ { "citation": [], "text": "Bias by story placement is when a story is placed in a position that is more likely to be seen by people." } ], "description": [ { "citation": [], "text": "This can be a deliberate choice by the person who is placing the story, or it can be an accidental choice." } ], "examples": [], "related_terms": [ { "citation": [], "text": "story" }, { "citation": [], "text": "position" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [ { "citation": [], "text": "Bias by story placement" } ], "term": "Bias by placement" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "the failure in a person's thinking to bring together the dichotomy of both positive and negative qualities of the self and others into a realistic whole." } ], "description": [ { "citation": [], "text": "Related to polarization" } ], "examples": [], "related_terms": [ { "citation": [], "text": "polarization" }, { "citation": [], "text": "dichotomy" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [ { "citation": [], "text": "splitting" } ], "term": "Black-and-white thinking" }, { "definitions": [ { "citation": [], "text": "Clickbait is a type of online content that is designed to lure readers to click on a link." } ], "description": [ { "citation": [ "(Potthast, Köpsel, Stein, & Hagen, 2016)" ], "text": "Clickbait often used language in which something unnamed is referred to, some emotional reaction is promised, some lack of knowledge is ascribed, or some authority is claimed" } ], "examples": [], "related_terms": [ { "citation": [ "(Potthast, Köpsel, Stein, & Hagen, 2016)" ], "text": "emotional reaction" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "online content" } ], "synonyms": [], "term": "Clickbait" }, { "definitions": [ { "citation": [], "text": "Bias by commission is a type of media bias in which media coverage favors one particular party or side in a dispute, often to the exclusion of the other party or side." } ], "description": [], "examples": [ { "citation": [], "text": "a news organization only interviews people who support a particular political candidate, and does not interview anyone who supports the other candidates." } ], "related_terms": [ { "citation": [], "text": "media coverage" }, { "citation": [], "text": "party" }, { "citation": [], "text": "side" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "media bias" } ], "synonyms": [ { "citation": [], "text": "Bias by commission" } ], "term": "Commission bias" }, { "definitions": [ { "citation": [ "(Nickerson, 1998)" ], "text": "compels us towards information that resonates with our existing beliefs" } ], "description": [], "examples": [], "related_terms": [ { "citation": [ "(Ross & Ward, 1996)" ], "text": "naïve realism" }, { "citation": [ "(Nickerson, 1998)" ], "text": "existing beliefs" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "cognitive biases" } ], "synonyms": [], "term": "confirmation bias" }, { "definitions": [ { "citation": [], "text": "Coverage bias refers to the (quantitative and qualitative) visibility of topics or entities in media coverage." } ], "description": [ { "citation": [], "text": "It is related to the tendency of the media to cover some stories and not others." }, { "citation": [], "text": "This can lead to a distorted view of reality, as the media is more likely to cover stories that are sensational or have a high potential for conflict." } ], "examples": [ { "citation": [], "text": "the tendency for the media to focus on negative stories." } ], "related_terms": [ { "citation": [], "text": "topics" }, { "citation": [], "text": "entities" }, { "citation": [], "text": "media coverage" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "media bias" } ], "synonyms": [], "term": "Coverage bias" }, { "definitions": [ { "citation": [], "text": "Misinformation and disinformation present erroneous information (either because it is false, incomplete and/or out of date), but the characteristic that differentiates them is that the misinformation does not have any misleading intentions, and the disinformation does." } ], "description": [ { "citation": [], "text": "disinformation is often spread deliberately, with the intention of misleading people" } ], "examples": [], "related_terms": [ { "citation": [], "text": "misinformation" }, { "citation": [], "text": "media bias" }, { "citation": [], "text": "fake news" }, { "citation": [], "text": "propaganda" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "erroneous information" } ], "synonyms": [], "term": "disinformation" }, { "definitions": [ { "citation": [], "text": "Fake news refers to the dissemination of information that has been purposely manipulated (i.e. fabricated) in order to cause damage or influence public opinion" }, { "citation": [], "text": "fake news are always false, while media bias can be true or false." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "media bias" }, { "citation": [], "text": "propaganda" }, { "citation": [], "text": "rumor" }, { "citation": [], "text": "disinformation" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "fake news" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "improperly applying a generalization to individual cases." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "generalization" }, { "citation": [], "text": "individual cases" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [], "term": "Fallacy of accident" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "Consists in inferring that something is true about a set or group just because it is true about one or more of its parts or components." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "set" }, { "citation": [], "text": "group" }, { "citation": [], "text": "parts or components" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [], "term": "Fallacy of composition" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "Consists in inferring that something is true about one or more of the parts of a compound because it is true about the compound of which it is a part." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "parts" }, { "citation": [], "text": "compound" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [], "term": "Fallacy of division" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "mislocating the cause of one phenomenon in another that is only seemingly related." } ], "description": [], "examples": [ { "citation": [], "text": "incorrectly link two events." } ], "related_terms": [ { "citation": [], "text": "cause" }, { "citation": [], "text": "phenomenon" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [ { "citation": [], "text": "non causa pro causa" } ], "term": "False cause fallacy" }, { "definitions": [ { "citation": [ "(Lazaridou, Krestel, & Naumann, 2017)" ], "text": "including quotes from both sides of an issue, even if one side is clearly more credible or trustworthy than the other." } ], "description": [ { "citation": [], "text": "This can lead to a biased portrayal of the issue, as the less credible side is given equal weight to the more credible side." } ], "examples": [], "related_terms": [ { "citation": [ "(Lazaridou, Krestel, & Naumann, 2017)" ], "text": "reported speech" }, { "citation": [], "text": "quotes" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "false sense of balance" }, { "definitions": [ { "citation": [], "text": "Flawed logic or faulty reasoning bias consists on leading to conclusions that are not justified by the given evidence." } ], "description": [], "examples": [], "related_terms": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "logical fallacies" }, { "citation": [], "text": "evidence" } ], "subtypes": [ { "citation": [], "text": "Hasty generalization" }, { "citation": [], "text": "over-generalization" }, { "citation": [], "text": "False cause fallacy" }, { "citation": [], "text": "Slippery slope" }, { "citation": [], "text": "Black-and-white thinking" }, { "citation": [], "text": "Fallacy of division" }, { "citation": [], "text": "Fallacy of composition" }, { "citation": [], "text": "Fallacy of accident" }, { "citation": [], "text": "Irrelevant conclusion fallacy" }, { "citation": [], "text": "Appeal to groupthink" }, { "citation": [], "text": "Appeal to authority" }, { "citation": [], "text": "Red Herring" } ], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [ { "citation": [], "text": "faulty reasoning bias" } ], "term": "Flawed logic bias" }, { "definitions": [ { "citation": [], "text": "emphasizing particular aspects of societal issues to mold public sentiment." } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "framing" }, { "definitions": [ { "citation": [], "text": "the stories that the media select or reject to report." } ], "description": [ { "citation": [], "text": "This can lead to a biased portrayal of events, as some stories may be deemed more important than others, regardless of their actual importance." } ], "examples": [], "related_terms": [ { "citation": [], "text": "stories" }, { "citation": [], "text": "media" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "media bias" } ], "synonyms": [ { "citation": [], "text": "selection bias" }, { "citation": [], "text": "agenda bias" } ], "term": "Gatekeeping bias" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "a claim is made based on evidence that is too small." } ], "description": [], "examples": [ { "citation": [], "text": "if a media outlet were to interview only three people at a protest and then claim ''The majority of attendees share the same view''" } ], "related_terms": [ { "citation": [], "text": "claim" }, { "citation": [], "text": "evidence" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "logical fallacies" } ], "synonyms": [ { "citation": [], "text": "over-generalization" } ], "term": "Hasty generalization" }, { "definitions": [ { "citation": [], "text": "the issuer presents the information in an partial way." } ], "description": [ { "citation": [], "text": "The author may be biased towards a certain ideology, which can influence the way they present information in their work." }, { "citation": [], "text": "The ideology bias is commonly detected in political issues, but it goes beyond the typical political compass (left v. right)." } ], "examples": [], "related_terms": [ { "citation": [], "text": "ideology" }, { "citation": [], "text": "political compass" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "media bias" } ], "synonyms": [ { "citation": [], "text": "stance" }, { "citation": [], "text": "framing bias" } ], "term": "Ideology bias" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "a conclusion is drawn, and it is not related to the argument." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "conclusion" }, { "citation": [], "text": "argument" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [], "term": "Irrelevant conclusion fallacy" }, { "definitions": [ { "citation": [], "text": "Labelling is a form of statement bias where the media outlet uses certain words or phrases to describe an individual, event, or organization in a way that conveys a particular opinion or perspective." } ], "description": [], "examples": [ { "citation": [], "text": "''illegal immigrant''" }, { "citation": [], "text": "''undocumented worker''" } ], "related_terms": [ { "citation": [], "text": "word choice" }, { "citation": [], "text": "opinion" }, { "citation": [], "text": "perspective" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "statement bias" } ], "synonyms": [], "term": "Labelling" }, { "definitions": [ { "citation": [ "Hamborg, Donnay et al. (2019)" ], "text": "media bias must both be intentional, i.e., reflect a conscious act or choice, and it must be sustained, i.e., represent a systematic tendency rather than an isolated incident." }, { "citation": [ "Spinde, Rudnitckaia et al. (2021)" ], "text": "Media bias is defined by researchers as slanted news coverage or internal bias, reflected in news articles." }, { "citation": [ "Gentzkow and Shapiro (2006)" ], "text": "The choice to slant information in this way (by selective omission, choice of words, and varying credibility ascribed to the primary source) is what we will mean in this paper by media bias." }, { "citation": [], "text": "a situation in which journalists slant information in a story to influence the opinion of the receiver, that is frequent and/or consistent for each media outlet or journalist." } ], "description": [ { "citation": [], "text": "media bias always has a journalistic format" }, { "citation": [], "text": "that is slanted, that is, it has the intention of influencing the opinion of the receiver in a particular direction" }, { "citation": [], "text": "that the same bias is frequent and/or consistent for each media/journalist" }, { "citation": [], "text": "journalists may add bias in their attempt to create memorable stories." }, { "citation": [], "text": "media bias is not always disinformation." } ], "examples": [], "related_terms": [ { "citation": [], "text": "opinion" }, { "citation": [], "text": "disinformation" }, { "citation": [], "text": "fake news" }, { "citation": [], "text": "propaganda" } ], "subtypes": [ { "citation": [], "text": "Spin bias" }, { "citation": [], "text": "Ideology bias" }, { "citation": [], "text": "Coverage bias" }, { "citation": [], "text": "Gatekeeping bias" }, { "citation": [], "text": "Statement bias" }, { "citation": [], "text": "Unsubstantiated claims bias" }, { "citation": [], "text": "Opinion statements presented as facts bias" }, { "citation": [], "text": "Sensationalism/emotionalism bias" }, { "citation": [], "text": "Ad hominem/mudslingin bias" }, { "citation": [], "text": "Mind reading bias" }, { "citation": [], "text": "Slant bias" }, { "citation": [], "text": "Omission bias" }, { "citation": [], "text": "Commission bias" }, { "citation": [], "text": "Bias by labeling and word choice" }, { "citation": [], "text": "Flawed logic bias" }, { "citation": [], "text": "Bias by placement" }, { "citation": [], "text": "Subjective qualifying adjectives bias" }, { "citation": [], "text": "Size allocation bias" }, { "citation": [], "text": "Source selection bias" }, { "citation": [], "text": "Omission of source attribution bias" }, { "citation": [], "text": "Picture selection bias" }, { "citation": [], "text": "Picture explanation bias" } ], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "media bias" }, { "definitions": [ { "citation": [], "text": "Media bias detection is a process of automatically identifying the presence of bias in a journalistic text." } ], "description": [ { "citation": [], "text": "most methods involve some combination of Natural Language Processing (NLP) and machine learning." }, { "citation": [], "text": "Bias detection is difficult because, as we already seen, there is no agreed-upon definition of what constitutes bias in journalism." }, { "citation": [], "text": "bias can be subtle and may not be easily detectable." } ], "examples": [], "related_terms": [ { "citation": [], "text": "Natural Language Processing (NLP)" }, { "citation": [], "text": "machine learning" }, { "citation": [], "text": "stance detection" }, { "citation": [], "text": "Propaganda detection" }, { "citation": [], "text": "Fake news detection" }, { "citation": [], "text": "Rumor detection" }, { "citation": [], "text": "Clickbait detection" }, { "citation": [], "text": "binary classification problem" }, { "citation": [], "text": "multi-class classification problem" }, { "citation": [], "text": "multi-label task" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "process" } ], "synonyms": [ { "citation": [], "text": "Bias detection" } ], "term": "Media bias detection" }, { "definitions": [ { "citation": [], "text": "Mind reading is a type of media bias that occurs in journalism when a journalist assumes that he or she knows what another person thinks, feels, or intends without actually speaking to that person." } ], "description": [ { "citation": [], "text": "This can lead to inaccuracies or even outright falsehoods being reported as fact." } ], "examples": [], "related_terms": [ { "citation": [], "text": "journalism" }, { "citation": [], "text": "falsehoods" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "media bias" } ], "synonyms": [], "term": "Mind reading bias" }, { "definitions": [ { "citation": [], "text": "Misinformation and disinformation present erroneous information (either because it is false, incomplete and/or out of date), but the characteristic that differentiates them is that the misinformation does not have any misleading intentions, and the disinformation does." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "disinformation" }, { "citation": [], "text": "misleading intentions" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "erroneous information" } ], "synonyms": [], "term": "misinformation" }, { "definitions": [ { "citation": [], "text": "morphosyntactic features related to grammar and sentence structure" } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "grammar" }, { "citation": [], "text": "sentence structure" }, { "citation": [], "text": "lexical features" }, { "citation": [], "text": "semantic features" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "linguistic features" } ], "synonyms": [], "term": "morphosyntactic features" }, { "definitions": [ { "citation": [ "(Yap, 2013)" ], "text": "mudslinging bias happens when people attack each other's character instead of debating the issue" } ], "description": [ { "citation": [], "text": "Such attacks divert attention away from the substantive issues and focus it on personal characteristics or actions, potentially leading the public to form opinions based on character assaults rather than policy strengths or weaknesses." } ], "examples": [], "related_terms": [ { "citation": [ "(Yap, 2013)" ], "text": "Ad Hominem bias" }, { "citation": [], "text": "character" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "mudslinging bias" }, { "definitions": [ { "citation": [ "(Ross & Ward, 1996)" ], "text": "the predisposition to perceive our interpretations of information as objective, leading us to conclude that those who hold differing opinions are either misinformed or biased" } ], "description": [], "examples": [], "related_terms": [ { "citation": [ "(Nickerson, 1998)" ], "text": "confirmation bias" }, { "citation": [ "(Ross & Ward, 1996)" ], "text": "interpretations of information" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "cognitive biases" } ], "synonyms": [], "term": "naïve realism" }, { "definitions": [ { "citation": [], "text": "The bias by omission is a type of media bias in which media outlets choose not to cover certain stories, topics or aspects of stories." } ], "description": [], "examples": [ { "citation": [], "text": "the lack of coverage of certain political candidates by the news media." } ], "related_terms": [ { "citation": [], "text": "stories" }, { "citation": [], "text": "topics" }, { "citation": [], "text": "media outlets" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "media bias" } ], "synonyms": [ { "citation": [], "text": "bias by omission" } ], "term": "Omission bias" }, { "definitions": [ { "citation": [], "text": "Omission of source attribution happens when a journalist does not back up his or her claim with a source, or the source is diffuse, or unspecific." } ], "description": [ { "citation": [], "text": "the omission of source attribution can be intentional, in order to protect the source's anonymity." } ], "examples": [ { "citation": [], "text": "''according to a source''" }, { "citation": [], "text": "''critics say''" }, { "citation": [], "text": "''experts believe''" } ], "related_terms": [ { "citation": [], "text": "claim" }, { "citation": [], "text": "source" }, { "citation": [], "text": "anonymity" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [ { "citation": [], "text": "Omission of source attribution" } ], "term": "Omission of source attribution bias" }, { "definitions": [ { "citation": [], "text": "a thought or belief about something or someone" } ], "description": [ { "citation": [], "text": "the line that separates bias from opinion depends on whether the journalist uses rhetorical artifacts that distort the information to support his opinion, or not." } ], "examples": [], "related_terms": [ { "citation": [], "text": "bias" }, { "citation": [], "text": "rhetorical artifacts" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "thought" }, { "citation": [], "text": "belief" } ], "synonyms": [], "term": "opinion" }, { "definitions": [ { "citation": [], "text": "Opinion statements presented as facts bias is based on the use of subjective language or statements under the guise of reporting objectively." } ], "description": [ { "citation": [], "text": "Subjective language is often used in editorials and opinions, as these are designed to persuade the reader to a particular viewpoint." } ], "examples": [], "related_terms": [ { "citation": [], "text": "subjective language" }, { "citation": [], "text": "reporting objectively" }, { "citation": [], "text": "opinions" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Opinion statements presented as facts bias" }, { "definitions": [ { "citation": [], "text": "the caption that is added next to the image can also add bias to the content." } ], "description": [ { "citation": [], "text": "the selection of images can affect the opinion of the reader" } ], "examples": [ { "citation": [ "(Gilens, 1996)" ], "text": "some US media outlets tends to exaggerates\nthe proportion of African Americans among the poor in their published photos (Gilens, 1996), causing the public’s to associate race and\npoverty" } ], "related_terms": [ { "citation": [], "text": "caption" }, { "citation": [], "text": "image" }, { "citation": [], "text": "Picture selection bias" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Picture explanation bias" }, { "definitions": [ { "citation": [], "text": "a type of cognitive bias that refers to the tendency for people to base their judgments on images that are presented to them, rather than on the actual content of the images." } ], "description": [ { "citation": [], "text": "Picture selection bias can lead people to make judgments about something without considering all of the information that is available." }, { "citation": [], "text": "This bias is similar to the word choice bias, but for images." } ], "examples": [ { "citation": [ "(Geske, 2016)" ], "text": "photos taken in the same manifestation can show totally different realities, they can already show violent or peaceful protesters, thus impacting the reader's opinion" } ], "related_terms": [ { "citation": [], "text": "word choice bias" }, { "citation": [], "text": "images" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "cognitive bias" } ], "synonyms": [ { "citation": [], "text": "Image selection bias" } ], "term": "Picture selection bias" }, { "definitions": [ { "citation": [], "text": "Presuppositions, by their nature, introduce information indirectly, making it less likely to be critically evaluated by readers." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "information" }, { "citation": [], "text": "news articles" }, { "citation": [], "text": "biases" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "Presuppositions" }, { "definitions": [ { "citation": [], "text": "propaganda is a deliberate attempt to influence public opinion." } ], "description": [ { "citation": [], "text": "Propaganda often uses a mixture of true and false information" } ], "examples": [], "related_terms": [ { "citation": [], "text": "public opinion" }, { "citation": [], "text": "media bias" }, { "citation": [], "text": "fake news" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "propaganda" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "introducing a new topic that is unrelated to the argument." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "topic" }, { "citation": [], "text": "argument" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [ { "citation": [], "text": "Ad ignorantiam" } ], "term": "Red Herring" }, { "definitions": [ { "citation": [], "text": "A rumor is a piece of information that is spread without any confirmation of its truth." }, { "citation": [], "text": "a rumor is a piece of information that is not verified yet" } ], "description": [ { "citation": [], "text": "In the context of social media, rumors spread very fast, and can often be difficult to distinguish from real news." } ], "examples": [], "related_terms": [ { "citation": [], "text": "fake news" }, { "citation": [ "(Shelke & Attar, 2019)" ], "text": "source detection" }, { "citation": [ "(Shelke & Attar, 2019)" ], "text": "social networks" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "piece of information" } ], "synonyms": [], "term": "rumor" }, { "definitions": [ { "citation": [], "text": "semantic features dealing with meaning." } ], "description": [ { "citation": [], "text": "semantic features such as Linguistic Inquiry, the Named Entity Recognition (NER), or Word Count (LIWC)" } ], "examples": [], "related_terms": [ { "citation": [], "text": "meaning" }, { "citation": [], "text": "lexical features" }, { "citation": [], "text": "morphosyntactic features" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "linguistic features" } ], "synonyms": [], "term": "semantic features" }, { "definitions": [ { "citation": [], "text": "Sensationalism is a type of bias where information is exaggerated in order to create a more emotional reaction." } ], "description": [ { "citation": [], "text": "This can be done by selectively choosing information that supports a certain view, while leaving out information that may contradict it." }, { "citation": [], "text": "Sensationalism is often used in the media to increase viewership or readership." } ], "examples": [], "related_terms": [ { "citation": [], "text": "emotional reaction" }, { "citation": [], "text": "viewership" }, { "citation": [], "text": "readership" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [ { "citation": [], "text": "Sensationalism" }, { "citation": [], "text": "emotionalism" } ], "term": "Sensationalism/emotionalism bias" }, { "definitions": [ { "citation": [], "text": "Slant bias is a type of bias that occurs when someone has preferences for one thing over another." } ], "description": [ { "citation": [], "text": "It can include cherry-picking information or data to support one side." }, { "citation": [], "text": "Slant bias can lead to people making judgments about others or situations without all of the facts, or it can cause them to misinterpret information." } ], "examples": [], "related_terms": [ { "citation": [], "text": "cherry-picking information" }, { "citation": [], "text": "preferences" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "bias" } ], "synonyms": [], "term": "Slant bias" }, { "definitions": [ { "citation": [], "text": "information that is presented in a way that is partial, or one-sided" } ], "description": [ { "citation": [], "text": "a new characteristic which can help us to better understand the relationship between information and disinformation" } ], "examples": [], "related_terms": [ { "citation": [], "text": "information" }, { "citation": [], "text": "disinformation" }, { "citation": [], "text": "media bias" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "characteristic" } ], "synonyms": [], "term": "slanted" }, { "definitions": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "an action will initiate a chain of events culminating in a predictable later event, without establishing or quantifying the relevant contingencies." } ], "description": [], "examples": [], "related_terms": [ { "citation": [], "text": "chain of events" }, { "citation": [], "text": "contingencies" } ], "subtypes": [], "supertypes": [ { "citation": [ "(Van Vleet, 2021)" ], "text": "fallacy" } ], "synonyms": [], "term": "Slippery slope" }, { "definitions": [ { "citation": [], "text": "Source selection bias is the tendency of journalists to choose sources that will support their stories, instead of choosing 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"citation": [], "text": "task" } ], "synonyms": [], "term": "Stance detection" }, { "definitions": [ { "citation": [], "text": "how articles choose to inform about certain entities/concepts." } ], "description": [ { "citation": [], "text": "This can be done through the use of loaded language or by presenting one side of an issue as the only side." } ], "examples": [ { "citation": [], "text": "referring to someone as an ''illegal immigrant'' rather than using the term ''undocumented worker'' creates a negative connotation and implies that the person is doing something wrong." }, { "citation": [], "text": "choosing to use the word ''abortion'' instead of ''choice'' or ''reproductive rights'' is more likely to create an emotional response in the reader and make them more likely to agree with the writer's position." } ], "related_terms": [ { "citation": [], "text": "loaded language" } ], "subtypes": [ { "citation": [ "(Hamborg, Zhukova, & Gipp, 2019)" ], "text": "Labelling" }, { 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"citation": [], "text": "Capturing the linking between the pairs of identified entities (or participants)" } ], "description": [ { "citation": [], "text": "Such semantic relations are usually structured in the form of < e 1 , rel, e 2 > triples, where e 1 and e 2 are named-entities, and rel is a relationship type" } ], "examples": [ { "citation": [], "text": "< John, pulled, a rabbit >" } ], "related_terms": [], "subtypes": [], "supertypes": [], "synonyms": [], "term": "relation extraction task" }, { "definitions": [ { "citation": [], "text": "a kind of temporal expression that requires further knowledge to be normalized" } ], "description": [], "examples": [ { "citation": [], "text": "yesterday" } ], "related_terms": [ { "citation": [], "text": "explicit" }, { "citation": [], "text": "implicit" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "relative temporal expressions" }, { "definitions": [ { "citation": [], "text": "extended DRT with the inclusion of discourse 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"supertypes": [], "synonyms": [], "term": "temporal reasoning" }, { "definitions": [ { "citation": [ "(Vijayarani et al. 2016)" ], "text": "break sentences into tokens, the smallest unit of a text" } ], "description": [], "examples": [], "related_terms": [], "subtypes": [], "supertypes": [ { "citation": [], "text": "lexical tasks" } ], "synonyms": [], "term": "Text tokenization" }, { "definitions": [ { "citation": [], "text": "built using visual elements like lines, graphs, icons, pictures, or other graphical resources used to depict the narrative" } ], "description": [ { "citation": [], "text": "more accessible for people of different degrees of general expertise" } ], "examples": [], "related_terms": [ { "citation": [], "text": "conceptual" } ], "subtypes": [], "supertypes": [ { "citation": [], "text": "levels" } ], "synonyms": [], "term": "visual level" } ] }, { "paper_id": "s40537-025-01077-x", "split": "train", "metadata": { "title": "Survey on terminology extraction from texts", "authors": [ "Kang Xu", "Yifan Feng", "Qiandi Li", "Zhenjiang Dong", "Jianxiang Wei" ], "publication_year": "2025", "doi": "10.1186/s40537-025-01077-x", "venue": "Journal of Big Data" }, "definition_records": [ { "definitions": [ { "citation": [], "text": "different meanings of the same term in various contexts" } ], "description": [ { "citation": [ "[231]" ], "text": "One of the major challenges currently faced in the field of terminology extraction" } ], "examples": [], "related_terms": [ { "citation": [], "text": "terminology extraction" } ], "subtypes": [], "supertypes": [], "synonyms": [], "term": "polysemy" } ] } ] }