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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Retweeting Activity on Twitter: Signs of Deception
verfasst von : Maria Giatsoglou, Despoina Chatzakou, Neil Shah, Christos Faloutsos, Athena Vakali
Erschienen in: Advances in Knowledge Discovery and Data Mining
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Given the re-broadcasts (i.e. retweets) of posts in Twitter, how can we spot fake from genuine user reactions? What will be the tell-tale sign — the connectivity of retweeters, their relative timing, or something else? High retweet activity indicates influential users, and can be monetized. Hence, there are strong incentives for fraudulent users to artificially boost their retweets’ volume. Here, we explore the identification of fraudulent and genuine retweet threads. Our main contributions are: (a) the discovery of
patterns
that fraudulent activity seems to follow (the “
triangles
” and “
homogeneity
” patterns, the formation of micro-clusters in appropriate feature spaces); and (b) “
RTGen
”, a realistic generator that mimics the behaviors of both honest and fraudulent users. We present experiments on a dataset of more than 6 million retweets crawled from Twitter.