Othertr
Spammer detection in social networks based on user behaviours
Darshika Niranjan Koggalahewa
Abstract
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.