NewsSlant

Analyzing Political News and Its Influence Through a Moral Lens

Bibliographic Data

ID22107404
AuthorsAmanul Haque (0000-0003-1388-6122, North Carolina State University), Munindar P Singh (0000-0003-3599-3893, North Carolina State University)
Year2024
Volume11
Issue3
Pages3329-3337
Publication date2024-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Computational Social Systems (JOURNAL)
Journal identifiersISSN: 2329-924X • E-ISSN: 2373-7476
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2023.3341910
OpenAlexW4390493117
LanguageEN
Citations received2
References cited59

Political news is often slanted toward its publisher’s ideology and seeks to influence readers by focusing on selected aspects of contentious social and political issues. We investigate political slants in news and their influence on readers by analyzing election-related news and readers’ reactions to the news on Twitter. To this end, we collected election-related news from six major U.S. news publishers who covered the 2020 U.S. presidential election. We computed each publisher’s political slant based on the favorability of its news toward the two major parties’ presidential candidates. We find that the election-related news coverage shows signs of political slant both in news headlines and on Twitter. The difference in news coverage of the two candidates between the left-leaning ( left ) and right-leaning ( right ) news publishers is statistically significant. The effect size is larger for the news on Twitter than for headlines. And, news on Twitter expresses stronger sentiments than the headlines. We identify moral foundations in readers’ reactions to the news on Twitter based on the moral foundation theory. Moral foundations in readers’ reactions to left and right differ statistically significantly, though the effects are small. Further, these shifts in moral foundations differ across social and political issues. User engagement on Twitter is higher for right than for left . We posit that an improved understanding of slant and influence can enable better ways to combat online political polarization

Fake news · Ideology · Media studies · Political science · Politics · Presidential election · Presidential system · Sociology · Hate Speech and Cyberbullying Detection · Law · Media Influence and Politics · Social Media and Politics

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