Computer Science – Social and Information Networks
Scientific paper
2010-11-16
Proceedings of the 20th international conference companion on World wide web, 249-252 (2011)
Computer Science
Social and Information Networks
Scientific paper
10.1145/1963192.1963301
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 introduce 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. We describe a Web service that leverages this framework to track political memes in Twitter and help detect astroturfing, smear campaigns, and other misinformation in the context of U.S. political elections. We present some cases of abusive behaviors uncovered by our service. Finally, we discuss promising preliminary results on the detection of suspicious memes via supervised learning based on features extracted from the topology of the diffusion networks, sentiment analysis, and crowdsourced annotations.
Conover Michael
Flammini Alessandro
Goncalves Bruno
Meiss Mark
Menczer Filippo
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