Publications

Corerank: Ranking to detect users involved in blackmarket-based collusive retweeting activities

Abstract

Twitter's popularity has fostered the emergence of various illegal user activities - one such activity is to artificially bolster visibility of tweets by gaining large number of retweets within a short time span. The natural way to gain visibility is time-consuming. Therefore, users who want their tweets to get quick visibility try to explore shortcuts - one such shortcut is to approach the blackmarket services, and gain retweets for their own tweets by retweeting other customers' tweets. Thus the users intrinsically become a part of a collusive ecosystem controlled by these services. In this paper, we propose CoReRank, an unsupervised framework to detect collusive users (who are involved in producing artificial retweets), and suspicious tweets (which are submitted to the blackmarket services) simultaneously. CoReRank leverages the retweeting (or quoting) patterns of users, and measures two scores - the 'credibility' of a user and …

Date
2019
Authors
Aditya Chetan, Brihi Joshi, Hridoy Sankar Dutta, Tanmoy Chakraborty
Book
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining
Pages
330-338