Badly evolved? Exploring long-surviving suspicious users on twitter

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Abstract

We study the behavior of long-lived eventually suspended accounts in social media through a comprehensive investigation of Arabic Twitter. With a threefold study of (i) the content these accounts post; (ii) the evolution of their linguistic patterns; and (iii) their activity evolution, we compare long-lived users versus short-lived, legitimate, and pro-ISIS users. We find that these long-lived accounts – though trying to appear normal – do exhibit significantly different behaviors from both normal and other suspended users. We additionally identify temporal changes and assess their value in supporting discovery of these accounts and find out that most accounts have actually being “hiding in plain sight” and are detectable early in their lifetime. Finally, we successfully apply our findings to address a series of classification tasks, most notably to determine whether a given account is a long-surviving account.

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APA

Alfifi, M., & Caverlee, J. (2017). Badly evolved? Exploring long-surviving suspicious users on twitter. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10539 LNCS, pp. 218–233). Springer Verlag. https://doi.org/10.1007/978-3-319-67217-5_14

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