Detecting and Tracking Political Abuse in Social Media

Authors

  • Jacob Ratkiewicz Indiana University
  • Michael Conover Indiana University
  • Mark Meiss Indiana University
  • Bruno Goncalves Indiana University
  • Alessandro Flammini Indiana University
  • Filippo Menczer Indiana University

Abstract

We study astroturf political campaigns on microblogging platforms: politically-motivated individuals and organizations that use multiple centrally-controlled accounts to create the appearance of widespread support for a candidate or opinion. We describe a machine learning framework that combines topological, content-based and crowdsourced features of information diffusion networks on Twitter to detect the early stages of viral spreading of political misinformation.  We present promising preliminary results with better than 96% accuracy in the detection of astroturf content in the run-up to the 2010 U.S. midterm elections.

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Published

2021-08-03

How to Cite

Ratkiewicz, J., Conover, M., Meiss, M., Goncalves, B., Flammini, A., & Menczer, F. (2021). Detecting and Tracking Political Abuse in Social Media. Proceedings of the International AAAI Conference on Web and Social Media, 5(1), 297-304. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14127