Sentiment Analysis of Malaysians Citizen's Emotion towards Cyberbullying in Twitter

Abstract

Cyberbullying, also known as cyber harassment, is a prevalent issue that significantly impacts the adolescent population in Malaysia. As a form of abusive online behavior, cyberbullying has expanded beyond the physical world into the virtual space, where monitoring activities and changes can be difficult. In 2020, Malaysia ranked second in Asia for cyberbullying among youths due to the widespread use of social media platforms, which have become an ideal breeding ground for negative behavior. This study aims to develop a web-based system that can analyze Malaysian citizens' emotional responses to cyberbullying using machine learning techniques. Additionally, emotional responses gained from Twitter will be characterized using emotional models. The machine learning life-cycle methodology will be implemented in this study. The findings revealed that anger emotion had the highest percentage compared to other emotions such as fear, happiness, love, sadness, and surprise. Expanding the scope of the study to include other social media platforms and demographic groups may provide a more comprehensive understanding of cyberbullying in Malaysia. These recommendations may improve the effectiveness of the web-based system and facilitate the development of more efficient strategies for preventing and mitigating the effects of cyberbullying in Malaysia.