Detecting Spammers on Twitter by Identifying User Behavior and Tweet-Based Features
Keywords:
C5.0, Spammer, Detection, Tweet-Based Features, Twitter,Abstract
Spam is a problem in the delivery of news and communication networks. It has various forms and definitions depend on the type of the network. With millions of users across worldwide, Twitter provides a variety of news and events. However, with the ease of dissemination of news, and allowing users to discuss the stories in their status, these services also open opportunities for another kind of spam. In this study, the proposed spammer detection classifies accounts into a spammer or non-spammer by studying/identifying user behavior and tweet-based features (number of followers, following, mentions and hashtag). The results showed that our proposed approach returns better scores comparing to the result of C5.0 algorithm.References
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