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.
CITATION STYLE
Ratkiewicz, J., Conover, M. D., Meiss, M., Gonçalves, B., Flammini, A., & Menczer, F. (2011). Detecting and Tracking Political Abuse in Social Media. In Proceedings of the 5th International AAAI Conference on Weblogs and Social Media, ICWSM 2011 (pp. 297–304). AAAI Press. https://doi.org/10.1609/icwsm.v5i1.14127
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