Analyzing spammers' social networks for fun and profit: a case study of cyber criminal ecosystem on twitter

Authors:
Chao Yang;Robert Harkreader;Jialong Zhang;Seungwon Shin;Guofei Gu
Affiliations:
Texas A&M University, College Station, USA;Texas A&M University, College Station, USA;Texas A&M University, College Station, USA;Texas A&M University, College Station, USA;Texas A&M University, College Station, USA
Venue:
Proceedings of the 21st international conference on World Wide Web
Year:
2012

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Abstract

In this paper, we perform an empirical analysis of the cyber criminal ecosystem on Twitter. Essentially, through analyzing inner social relationships in the criminal account community, we find that criminal accounts tend to be socially connected, forming a small-world network. We also find that criminal hubs, sitting in the center of the social graph, are more inclined to follow criminal accounts. Through analyzing outer social relationships between criminal accounts and their social friends outside the criminal account community, we reveal three categories of accounts that have close friendships with criminal accounts. Through these analyses, we provide a novel and effective criminal account inference algorithm by exploiting criminal accounts' social relationships and semantic coordinations.