language:
- en
tags:
- psycholinguistics
- eye-tracking
- reading
- lexical-frequency
- word-predictability
- affective-norms
- valence
- arousal
- dominance
- computational-linguistics
- reproducible-research
pretty_name: AffLex-Provo
AffLex-Provo
An Integrated Research Repository for Lexical and Affective Influences on Eye Movements During Natural Reading
Creator and Computational Developer: Mohit Gupta
Institution: University of Illinois Urbana-Champaign
Repository: https://huggingface.co/datasets/mohitg2/AffLex-Provo
Overview
AffLex-Provo is a computational psycholinguistics research repository integrating eye-tracking observations, lexical frequency measures, contextual word predictability, and affective word norms.
The research resources are constructed using three established datasets:
- Provo Corpus — Luke and Christianson (2018).
- SUBTLEX-US — Brysbaert and New (2009).
- Affective Norms — Warriner et al. (2013).
The repository includes original preprocessing code, integrated research datasets, statistical analysis scripts, research outputs, and reproducibility documentation.
Research Datasets
The computational triangulation pipeline produces three primary datasets:
| Dataset | Description |
|---|---|
| Master Provo | Integrated research dataset retaining available lexical and affective information |
| Lexical Provo | Dataset supporting analyses of lexical predictors |
| Affective Provo | Dataset supporting analyses of lexical and affective predictors |
Licensing
Original Python and R software is licensed under the MIT License, where indicated.
Eligible original research data contributions and documentation are licensed under CC BY 4.0, where indicated.
Third-party research datasets remain subject to their original rights and redistribution conditions.
Citation
Researchers using the original AffLex-Provo computational resources are strongly requested to cite:
Gupta, M. (2026). AffLex-Provo: Integrated lexical and affective research datasets and computational resources [Data set and software]. Hugging Face.
Repository DOI: Pending assignment.
Researchers should also cite the original datasets relevant to their work.
Associated Publication
Gupta, M., & Christianson, K. (in press).
Beyond Word Length, Frequency, and Predictability: Affective Properties Predict Eye Movement in Reading.
Reading Research Quarterly.
Article DOI: Pending assignment.