Access Restriction

Author Ratkiewicz, J. ♦ Conover, M. D. ♦ Meiss, M. ♦ Flammini, A. ♦ Menczer, F.
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Widespread Support ♦ Viral Spreading ♦ U.s. Midterm Election ♦ Social Medium ♦ Early Stage ♦ Political Abuse ♦ Political Misinformation ♦ Politically-motivated Individual ♦ Multiple Centrally-controlled Account ♦ Astroturf Political Campaign ♦ Preliminary Result ♦ Astroturf Content ♦ Information Diffusion Network ♦ Crowdsourced Feature
Description We study astroturf political campaigns on microblogging platforms: politically-motivated individuals and organiza-tions that use multiple centrally-controlled accounts to create the appearance of widespread support for a candidate or opin-ion. We describe a machine learning framework that com-bines 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. 1
In Proceedings of ICWSM
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2011-01-01