Microblogging

Pedagogy

Politics

Internet privacy

World Wide Web

Political science

Psychology

Tracking (education)

Data science

Misinformation

Fake news

Public relations

Computer science

Social media

Computer security

Proceedings of the International AAAI Conference on Web and Social Media

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.

Detecting and Tracking Political Abuse in Social Media