Detection of misbehaving individuals in social networks using overlapping communities and machine learning

Detecting misbehavior in social networks is essential for maintaining trust and reliability in online communities. Traditional methods of identification often rely on individual attributes or structural network properties, which may overlook subtle or complex misbehavior patterns. This paper introdu...

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Bibliographic Details

Published in:	Journal of King Saud University: Computer and Information Sciences
Main Authors:	Wejdan Alshlahy, Delel Rhouma
Format:	Article
Language:	English
Published:	Springer 2024-07-01
Subjects:	Social network Graph mining Overlapping community Contextual anomaly Structural anomaly Anomaly detection
Online Access:	http://www.sciencedirect.com/science/article/pii/S131915782400199X