网络欺凌检测综述

Cyberbullying has attracted the increasing attention among researchers. Social and computer science researchers have explored cyberbullying from various perspectives. This paper surveys the existing work on cyberbullying detection in social and computer science domains. It first introduces the basic research problems and characteristics of cyberbullying; second, it discusses a variety of machine learning algorithms for cyberbullying detection, including supervised learning, weakly supervised learning, rule-based and deep learning algorithms; and third, it summarizes 12 existing datasets used in cyberbullying detection and the popular metrics for detection performance. Finally, the paper analyzes the potential research from several aspects, such as cyberbullying detection approaches based on heterogeneous information network, auxiliary information fusion, and psychological characteristics.