Characterizing social media manipulation in the 2020 U.S. presidential election

  • Emilio Ferrara Information Sciences Institute, University of Southern California
  • Herbert Chang
  • Emily Chen
  • Goran Muric
  • Jaimin Patel

Abstract

Democracies are postulated upon the ability to carry out fair elections, free from any form of interference or manipulation. Social media have been reportedly used to distort public opinion nearing election events in the United States and beyond. With over 240 million election-related tweets recorded between 20 June and 9 September 2020, in this study we chart the landscape of social media manipulation in the context of the upcoming 3 November 2020 U.S. presidential election. We focus on characterizing two salient dimensions of social media manipulation, namely (i) automation (e.g., the prevalence of bots), and (ii) distortion (e.g., manipulation of narratives, injection of conspiracies or rumors). Despite being outnumbered by several orders of magnitude, just a few thousands of bots generated spikes of conversations around real-world political events in all comparable with the volume of activity of humans. We discover that bots also exacerbate the consumption of content produced by users with their same political views, worsening the issue of political echo chambers. Furthermore, coordinated efforts carried out by Russia, China and other countries are hereby characterized. Finally, we draw a clear connection between bots, hyper-partisan media outlets, and conspiracy groups, suggesting the presence of systematic efforts to distort political narratives and propagate disinformation. Our findings may have impactful implications, shedding light on different forms of social media manipulation that may, altogether, ultimately pose a risk to the integrity of the election.

Published
2020-10-19
How to Cite
Ferrara, E., Chang, H., Chen, E., Muric, G., & Patel, J. (2020). Characterizing social media manipulation in the 2020 U.S. presidential election. First Monday, 25(11). https://doi.org/10.5210/fm.v25i11.11431