Spammer detection in social networks based on user behaviours

Özet

This thesis unveils a novel methodology for identifying social spammers through an innovative analysis of user behaviours. The battle against social spammers has emerged as a formidable obstacle in online social networks (OSNs). Although classification-based approaches have garnered significant popularity in combating social spammers, they are plagued by persistent challenges related to data labelling and spam drift. To overcome these obstacles, this thesis introduces a pure unsupervised approach for detecting social spammers, along with a novel strategy for effectively managing spammer drift in OSNs.

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• davettezler:f2225b69-fd47-4e71-a804-5d388ca548f02026-07-10T09:07:30.603820+03:00