关键词: 社交网络, 异常用户, 异常识别技术, 机器学习

Abstract: With the rapid development of the Internet, social network has become an important social tool in daily life. However, the abnormal users in social networks emerge in an endless stream, and its harm is becoming increasingly serious. Therefore, identifying and detecting abnormal users in social networks plays an important role in improving the user experience and maintaining a good network environment. This paper introduces different types of abnormal social network users, and introduces the research progress of each type of abnormal user. Finally, it summarizes the anomaly detection methods, and divides the anomaly detection technologies in social networks into categories, clustering, statistics, information theory, hybrid and graphs, and the advantages and disadvantages of these six technologies are compared, which can help people understand abnormal users and anomaly detection technologies in social networks, and provides ideas for solving abnormal problems.

Key words: social network, abnormal user, abnormity recognition technology, machine learning