Resources
Most recent models are published on Huggingface
[Benchmark, GitHub] MBIB – the first Media Bias Identification Benchmark Task and Dataset Collection
[Dataset, Huggingface] Anno-lexical (Lexical bias)
[Dataset, GitHub] BABE – Bias Annotations By Experts
[Dataset, Paper] BAT – Bias And Twitter
[Scale/Questionnaire to measure bias perception] Do You Think It’s Biased? How To Ask For The Perception Of Media Bias (A set of tested questions to assess media bias perception to be used in any bias-related research)
[Dataset, Zenodo] MBIC -A Media Bias Annotation Dataset Including Annotator Characteristics
Publications
2020
Garz, Marcel; Sörensen, Jil; Stone, Daniel F.
Partisan selective engagement: Evidence from Facebook Journal Article
In: Journal of Economic Behavior & Organization, vol. 177, pp. 91-108, 2020, ISSN: 0167-2681.
Abstract | Links | BibTeX | Tags: Filter bubble, media bias, Polarization, Political immunity, Social media
@article{GARZ202091,
title = {Partisan selective engagement: Evidence from Facebook},
author = {Marcel Garz and Jil Sörensen and Daniel F. Stone},
url = {https://www.sciencedirect.com/science/article/pii/S0167268120302079},
doi = {https://doi.org/10.1016/j.jebo.2020.06.016},
issn = {0167-2681},
year = {2020},
date = {2020-01-01},
journal = {Journal of Economic Behavior & Organization},
volume = {177},
pages = {91-108},
abstract = {This study investigates the effects of variation in “congeniality” of news on Facebook user engagement (likes, shares, and comments). We compile an original data set of Facebook posts by 84 German news outlets on politicians that were investigated for criminal offenses from January 2012 to June 2017. We also construct an index of each outlet's media slant by comparing the language of the outlet with that of the main political parties, which allows us to measure the congeniality of the posts. We find that user engagement with congenial posts is higher than with uncongenial ones, especially in terms of likes. The within-outlet, within-topic design allows us to infer that the greater engagement with congenial news is likely driven by psychological and social factors, rather than a desire for accurate or otherwise instrumental information.},
keywords = {Filter bubble, media bias, Polarization, Political immunity, Social media},
pubstate = {published},
tppubtype = {article}
}