Identifying Hidden Factors for Verbal Harassment Comments on Social Media

Research on crimes committed on social media platforms is growing fast as more platforms are made available to the general public (Facebook, Instagram, Twitter, etc.). The focus of this study is on offenses involving verbal abuse directed at a specific individual or group of individuals. As social media platforms continue to develop at an astronomical pace, users’ mental health is being adversely affected as a result. Analysis of public comments is the primary focus of the research, which aims to identify and remove any offensive or improper comments from them. The findings of this study provide a possible solution to this particular issue. We evaluate approximately 13 research papers on verbal harassment comments on social media. In this paper’s review, we attempt to identify and analyze the concealed factors. We also attempt to introduce some tools and algorithms that are used to identify harassment-related comments. We also conducted a survey; the survey questions represent the percentage of social media users who face verbal harassment. In future work, we will attempt to implement LSTM-based comment detectors for identifying instances of online harassment. Also, we provide some justifications for selecting the LSTM algorithm as our future implementation technique.