Resources & Publications
All members of the network can share their recent work on media bias here.
Resources
Most recent models are published on Huggingface
[Benchmark, GitHub] MBIB – the first Media Bias Identification Benchmark Task and Dataset Collection
[Dataset, GitHub] BABE – Bias Annotations By Experts
[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}
}
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.
Garz, Marcel; Sood, Gaurav; Stone, Daniel F.; Wallace, Justin
The supply of media slant across outlets and demand for slant within outlets: Evidence from US presidential campaign news Journal Article
In: European Journal of Political Economy, vol. 63, pp. 101877, 2020, ISSN: 0176-2680.
Abstract | Links | BibTeX | Tags: Horse race news, media bias, Media slant, Motivated beliefs, Polarization, Selective exposure
@article{GARZ2020101877,
title = {The supply of media slant across outlets and demand for slant within outlets: Evidence from US presidential campaign news},
author = {Marcel Garz and Gaurav Sood and Daniel F. Stone and Justin Wallace},
url = {https://www.sciencedirect.com/science/article/pii/S0176268020300252},
doi = {https://doi.org/10.1016/j.ejpoleco.2020.101877},
issn = {0176-2680},
year = {2020},
date = {2020-01-01},
journal = {European Journal of Political Economy},
volume = {63},
pages = {101877},
abstract = {We conduct across-outlet and within-outlet (and within-topic) analyses of “congenially” slanted news. We study “horse race” news (news on candidates' chances in an upcoming election) from six major online outlets for the 2012 and 2016 US presidential campaigns. We find robust evidence that horse race headlines were slanted congenially with respect to the preferences of the outlets' typical readers. However, evidence of congenial slant in the timing and frequency of horse race stories is weaker. We also find limited evidence of greater within-outlet demand for headlines most congenial to outlets' typical readers, and somewhat stronger evidence of greater demand for relatively uncongenial headlines. We discuss how various aspects of our results are consistent with each of the major mechanisms driving slant studied in the theoretical literature, and may help explain when each mechanism is more likely to come into play. In particular, readers may be more likely to click on uncongenial headlines due to inferring that these stories are particularly informative when they stand in contrast to an outlet's typically congenial slant.},
keywords = {Horse race news, media bias, Media slant, Motivated beliefs, Polarization, Selective exposure},
pubstate = {published},
tppubtype = {article}
}
We conduct across-outlet and within-outlet (and within-topic) analyses of “congenially” slanted news. We study “horse race” news (news on candidates' chances in an upcoming election) from six major online outlets for the 2012 and 2016 US presidential campaigns. We find robust evidence that horse race headlines were slanted congenially with respect to the preferences of the outlets' typical readers. However, evidence of congenial slant in the timing and frequency of horse race stories is weaker. We also find limited evidence of greater within-outlet demand for headlines most congenial to outlets' typical readers, and somewhat stronger evidence of greater demand for relatively uncongenial headlines. We discuss how various aspects of our results are consistent with each of the major mechanisms driving slant studied in the theoretical literature, and may help explain when each mechanism is more likely to come into play. In particular, readers may be more likely to click on uncongenial headlines due to inferring that these stories are particularly informative when they stand in contrast to an outlet's typically congenial slant.
2018
Babaei, Mahmoudreza; Kulshrestha, Juhi; Chakraborty, Abhijnan; Benevenuto, Fabrício; Gummadi, Krishna P.; Weller, Adrian
Purple Feed: Identifying High Consensus News Posts on Social Media Proceedings Article
In: Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, pp. 10–16, Association for Computing Machinery, New Orleans, LA, USA, 2018, ISBN: 9781450360128.
Abstract | Links | BibTeX | Tags: audience leaning based features, consensus, news consumption in social media, Polarization, purple feed
@inproceedings{10.1145/3278721.3278761,
title = {Purple Feed: Identifying High Consensus News Posts on Social Media},
author = {Mahmoudreza Babaei and Juhi Kulshrestha and Abhijnan Chakraborty and Fabrício Benevenuto and Krishna P. Gummadi and Adrian Weller},
url = {https://doi.org/10.1145/3278721.3278761},
doi = {10.1145/3278721.3278761},
isbn = {9781450360128},
year = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society},
pages = {10–16},
publisher = {Association for Computing Machinery},
address = {New Orleans, LA, USA},
series = {AIES '18},
abstract = {Although diverse news stories are actively posted on social media, readers often focus on the news which reinforces their pre-existing views, leading to 'filter bubble' effects. To combat this, some recent systems expose and nudge readers toward stories with different points of view. One example is the Wall Street Journal's 'Blue Feed, Red Feed' system, which presents posts from biased publishers on each side of a topic. However, these systems have had limited success. We present a complementary approach which identifies high consensus 'purple' posts that generate similar reactions from both 'blue' and 'red' readers. We define and operationalize consensus for news posts on Twitter in the context of US politics. We show that high consensus posts can be identified and discuss their empirical properties. We present a method for automatically identifying high and low consensus news posts on Twitter, which can work at scale across many publishers. To do this, we propose a novel category of audience leaning based features, which we show are well suited to this task. Finally, we present our 'Purple Feed' system which highlights high consensus posts from publishers on both sides of the political spectrum.},
keywords = {audience leaning based features, consensus, news consumption in social media, Polarization, purple feed},
pubstate = {published},
tppubtype = {inproceedings}
}
Although diverse news stories are actively posted on social media, readers often focus on the news which reinforces their pre-existing views, leading to 'filter bubble' effects. To combat this, some recent systems expose and nudge readers toward stories with different points of view. One example is the Wall Street Journal's 'Blue Feed, Red Feed' system, which presents posts from biased publishers on each side of a topic. However, these systems have had limited success. We present a complementary approach which identifies high consensus 'purple' posts that generate similar reactions from both 'blue' and 'red' readers. We define and operationalize consensus for news posts on Twitter in the context of US politics. We show that high consensus posts can be identified and discuss their empirical properties. We present a method for automatically identifying high and low consensus news posts on Twitter, which can work at scale across many publishers. To do this, we propose a novel category of audience leaning based features, which we show are well suited to this task. Finally, we present our 'Purple Feed' system which highlights high consensus posts from publishers on both sides of the political spectrum.
