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The rise of social media platforms has led to an increase in cyber-aggressivebehavior, encompassing a broad spectrum of hostile behavior, includingcyberbullying, online harassment, and the dissemination of offensive and hatespeech. These behaviors have been associated with significant societalconsequences, ranging from online anonymity to real-world outcomes such asdepression, suicidal tendencies, and, in some instances, offline violence.Recognizing the societal risks associated with unchecked aggressive content,this paper delves into the field of Aggression Content Detection and BehavioralAnalysis of Aggressive Users, aiming to bridge the gap between disparatestudies. In this paper, we analyzed the diversity of definitions and proposed aunified cyber-aggression definition. We examine the comprehensive process ofAggression Content Detection, spanning from dataset creation, feature selectionand extraction, and detection algorithm development. Further, we review studieson Behavioral Analysis of Aggression that explore the influencing factors,consequences, and patterns associated with cyber-aggressive behavior. Thissystematic literature review is a cross-examination of content detection andbehavioral analysis in the realm of cyber-aggression. The integratedinvestigation reveals the effectiveness of incorporating sociological insightsinto computational techniques for preventing cyber-aggressive behavior.Finally, the paper concludes by identifying research gaps and encouragingfurther progress in the unified domain of socio-computational aggressivebehavior analysis.

A Survey on Online User Aggression: Content Detection and Behavioral Analysis on Social Media