Die Free or Live Hard? Empirical Evaluation and New Design for Fighting Evolving Twitter Spammers Conference Paper uri icon

abstract

  • Due to the significance and indispensability of detecting and suspending Twitter spammers, many researchers along with the engineers in Twitter Corporation have devoted themselves to keeping Twitter as spam-free online communities. Meanwhile, Twitter spammers are also evolving to evade existing detection techniques. In this paper, we make an empirical analysis of the evasion tactics utilized by Twitter spammers, and then design several new and robust features to detect Twitter spammers. Finally, we formalize the robustness of 24 detection features that are commonly utilized in the literature as well as our proposed ones. Through our experiments, we show that our new designed features are effective to detect Twitter spammers, achieving a much higher detection rate than three state-of-the-art approaches [35,32,34] while keeping an even lower false positive rate. 2011 Springer-Verlag.

published proceedings

  • Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

author list (cited authors)

  • Yang, C., Harkreader, R. C., & Gu, G.

citation count

  • 132

complete list of authors

  • Yang, Chao||Harkreader, Robert Chandler||Gu, Guofei

publication date

  • January 2011