Quantifying Political Leaning from Tweets and Retweets

Authors

  • Felix Ming Fai Wong Princeton University
  • Chee Wei Tan City University of Hong Kong
  • Soumya Sen Princeton University
  • Mung Chiang Princeton University

DOI:

https://doi.org/10.1609/icwsm.v7i1.14422

Keywords:

media, politics, elections, convex optimization

Abstract

Media outlets and pundits have been quick to embrace online social networks to disseminate their own opinions. But pundits’ opinions and news coverage are often marked by a clear political bias, as widely evidenced during the fiercely contested
2012 U.S. presidential elections. Given the wide availability of such data from sites like Twitter, a natural question is whether we can quantify the political leanings of media outlets using OSN data. In this work, by drawing a correspondence between tweeting and retweeting behavior, we formulate political leaning estimation as an ill-posed linear inverse problem. The result is a simple and scalable approach that does not require explicit knowledge of the network topology. We evaluate our method with a dataset of 119 million election-related tweets collected from April to November, and use it to study the political leaning of prominent tweeters and media sources.

Downloads

Published

2021-08-03

How to Cite

Wong, F. M. F., Tan, C. W., Sen, S., & Chiang, M. (2021). Quantifying Political Leaning from Tweets and Retweets. Proceedings of the International AAAI Conference on Web and Social Media, 7(1), 640-649. https://doi.org/10.1609/icwsm.v7i1.14422