Measuring COVID-19 Related Media Consumption on Twitter
Cai Yang

TL;DR
This study analyzes COVID-19 related media consumption on Twitter across different countries, using quantitative metrics to understand patterns and their relation to offline political preferences during the pandemic.
Contribution
It introduces a novel quantitative approach to measure and analyze global COVID-19 media consumption on Twitter, filling a gap in international-scale research.
Findings
First-of-its-kind global analysis of COVID-19 media consumption on Twitter.
Reveals geographic and political patterns in media engagement during the pandemic.
Provides a new metric 'interaction' for quantifying media consumption.
Abstract
The COVID-19 pandemic has been affecting the world dramatically ever since 2020. The minimum availability of physical interactions during the lockdown has caused more and more people to turn to online activities on social media platforms. These platforms have provided essential updates regarding the pandemic, serving as bridges for communications. Research on studying these communications on different platforms emerges during the meantime. Prior studies focus on areas such as topic modeling, sentiment analysis and prediction tasks such as predicting COVID-19 positive cases, misinformation spread, etc. However, online communications with media outlets remain unexplored on an international scale. We have little knowledge about the patterns of the media consumption geographically and their association with offline political preference. We believe addressing these questions could help…
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Taxonomy
TopicsMisinformation and Its Impacts · Sentiment Analysis and Opinion Mining
