The Shapes of the Fourth Estate During the Pandemic: Profiling COVID-19 News Consumption in Eight Countries
Cai Yang, Lexing Xie, Siqi Wu

TL;DR
This study analyzes COVID-19 news consumption and political leanings across eight countries using Twitter data, revealing consistent audience bias patterns and introducing new media bias estimation methods.
Contribution
It introduces a novel approach to measure media bias through audience leaning scores derived from Twitter retweet networks and validates these against existing bias scores.
Findings
Bi-modal user leaning distributions in six countries
Cross-country retweeting does not cross partisan lines
New bias scores correlate strongly with existing measures
Abstract
News media is often referred to as the Fourth Estate, a recognition of its political power. New understandings of how media shape political beliefs and influence collective behaviors are urgently needed in an era when public opinion polls do not necessarily reflect election results and users influence each other in real-time under algorithm-mediated content personalization. In this work, we measure not only the average but also the distribution of audience political leanings for different media across different countries. The methodological components of these new measures include a high-fidelity COVID-19 tweet dataset; high-precision user geolocation extraction; and user political leaning estimated from the within-country retweet networks involving local politicians. We focus on geolocated users from eight countries, profile user leaning distribution for each country, and analyze…
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Taxonomy
TopicsMisinformation and Its Impacts · Media Influence and Politics · Social Media and Politics
