User-focused analysis and characterization of cyberbullying

Abstract

While the rapid spread of social media has greatly advanced social interaction, aggressive behavior, such as abuse, has become a problem. In some cases, abuse can lead to mental illness or suicide, and it is important to understand the mechanisms of aggressive behavior and detect them in society. Text-based analysis of attacks on social media has become difficult to characterize due to the shortness and ambiguity of the sentences. In order to solve this problem, user-based analysis of attacks has been conducted, but the results are diverse and no certain knowledge has been obtained. In this study, we analyzed the attack tweets extracted from the sampling data of Japanese Twitter using sentence-BERT in order to classify the attacks into several types based on the nature of the users and their network relationships, and to clarify their characteristics. We found that most of the attacks occurred when the users' networks were close to each other, and that the users who attacked distant users on their networks tended to post many negative tweets. We also found that the users who attacked distant users tended to post more negative messages.