Analysis and Development of Information System for Cyberbullying Tendency on Twitter Social Media Using the Naïve Bayes Approach
Yulius Hari, Maharani Kusuma Putri, Darmanto Darmanto · International Journal of Research and Innovation in Social Science · 2024
Social media news becomes information read by thousands of individuals worldwide. Social media users in society have the freedom to post comments based on their perspectives, and the larger community can see whether these remarks are positive or negative. However, many comments are not constructive, and many of them lead to bullying. Unsupervised communication in the social realm can lead to a variety of deviations, which are commonly referred to as cyberbullying; several incidents of cyberbullying have happened. This research can also be used to express negative feelings about someone by writing them down and sharing them on social media. Methodology used in this research is following the System Development Life Cycles and based on naïve Bayes approach to classify the expression whenever it’s a bullying or not. From the research finding the system can help to mitigate the bullying tendencies in social media, although the system cannot predict whenever its actual bullying or a pun made by friends.