| ---
|
| dataset_info:
|
| features:
|
| - name: text
|
| dtype: string
|
| - name: label
|
| dtype: string
|
| - name: id
|
| dtype: int64
|
| splits:
|
| - name: train
|
| num_bytes: 1148348
|
| num_examples: 9641
|
| - name: test
|
| num_bytes: 317153
|
| num_examples: 2679
|
| - name: val
|
| num_bytes: 125692
|
| num_examples: 1072
|
| download_size: 1048892
|
| dataset_size: 1591193
|
| configs:
|
| - config_name: default
|
| data_files:
|
| - split: train
|
| path: data/train-*
|
| - split: test
|
| path: data/test-*
|
| - split: val
|
| path: data/val-*
|
| task_categories:
|
| - text-classification
|
| language:
|
| - ru
|
| tags:
|
| - russian
|
| - sentiment_analysis
|
| - social_media
|
| size_categories:
|
| - 1K<n<10K
|
| ---
|
| |
| ## Disclaimer |
|
|
| This is a reupload of the dataset, which is originally stored on [GitHub](https://github.com/sismetanin/rusentitweet). We only added a `val` split that is 10% of the original `train` split for a convenience. Next the original description is following. |
|
|
| # RuSentiTweet: A Sentiment Analysis Dataset of General Domain Tweets in Russian |
|
|
| This repository contains RuSentiTweet, a sentiment analysis dataset of 13,392 general domain tweets in Russian, which were created within the paper ["RuSentiTweet: A Sentiment Analysis Dataset of General Domain Tweets in Russian"](https://doi.org/10.7717/peerj-cs.1039). RuSentiTweet was manually annotated (moderate inter-rater agreement) using [RuSentiment](https://aclanthology.org/C18-1064/) guidelines into 5 classes: Positive, Neutral, Negative, Speech Act, and Skip. As a source of data, we used [Twitter Stream Grab](https://archive.org/details/twitterstream), a historical collection of tweets obtained from the general Twitter API stream. |
|
|
| Citation: |
| ``` |
| @article{smetanin2022rusetitweet, |
| title = {RuSentiTweet: A Sentiment Analysis Dataset of General Domain Tweets in Russian}, |
| author = {Sergey Smetanin}, |
| journal = {PeerJ Computer Science}, |
| volume = {8}, |
| pages = {e1039}, |
| year = {2022}, |
| doi = {10.7717/peerj-cs.1039}, |
| publisher = {PeerJ Inc.} |
| } |
| ``` |
