Forensic Linguistic Study on Cases of Hate Speech on Social Media

Abstract

Hate speech refers to widespread verbal insults in cyberspace. This happens because most people consider comments and insults in cyberspace to be normal in public spaces. Based on these problems, researchers are interested in studying more deeply the cases of hate that have resulted in legal cases on social media. This research is qualitative research using descriptive analysis methods which aims to examine hatred of hatred on social media in the form of posts or comments which lead to legal cases. Data collection methods are carried out through several techniques. First, researchers searched for data through electronic media 'Google' and 'You-Tube'. The search keywords used were "Cases of Hate Speech on Social Media". The search was carried out on June 15, 2024 regarding these keywords. Second, the data collection technique continues with the observation method. The listening method is used to observe and listen to evidence that makes the suspect involved in a legal case. Then, the data was reprocessed using a verbatim technique. Meanwhile, the instruments used to collect data are human instruments. The data was analyzed semantically and pragmatically using the matching and matching method. The research results show that most cases of hate originate from posts or statuses uploaded directly to the owner/perpetrator's account. The data studied consisted of three cases which were analyzed using forensic linguistic studies. The results of the study show that the form of hatred that occurs is in the form of posts aimed at triggering other parties. Apart from that, there are those who deliberately carry out SARA actions. Therefore, the perpetrator is subject to a crime based on evidence from the witness who reported it.