ABSTRACT
Online social media are complementing and in some cases replacing person-to-person social interaction and redefining the diffusion of information. In particular, microblogs have become crucial grounds on which public relations, marketing, and political battles are fought. We demonstrate a web service that tracks political memes in Twitter and helps detect astroturfing, smear campaigns, and other misinformation in the context of U.S. political elections. We also present some cases of abusive behaviors uncovered by our service. Our web service is based on an extensible framework that will enable the real-time analysis of meme diffusion in social media by mining, visualizing, mapping, classifying, and modeling massive streams of public microblogging events.
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- C. Grier, K. Thomas, V. Paxson, and M. Zhang. @spam: the underground on 140 characters or less. In Proc. of the 17th ACM Conf. on Computer and Communications Security (CCS), pages 27--37, 2010. Google Scholar
Digital Library
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- J. Ratkiewicz, M. Conover, M. Meiss, B. Gonçalves, S. Patil, A. Flammini, and F. Menczer. Detecting and tracking the spread of astroturf memes in microblog streams. Technical Report arXiv:1011.3768 {cs.SI}, CoRR, 2010.Google Scholar
- A. H. Wang. Don't follow me: Twitter spam detection. In Proc. 5th International Conf. on Security and Cryptography (SECRYPT), 2010.Google Scholar
- S. Yardi, D. Romero, G. Schoenebeck, and danah boyd. Detecting spam in a Twitter network. First Monday, 15(1), 2009.Google Scholar
Index Terms
- Truthy: mapping the spread of astroturf in microblog streams
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