“DETECTION OF CYBERBULLYING SPAM MAILS”

Abstract

Cyberbullying is a serious problem that affects many young people, and social networking sites are a common platform for this behavior. The use of technology as a medium for bullying has increased in recent years, and this underscores the need for research to develop intelligent systems that can automatically detect and prevent potentially harmful messages. The work on constructing and annotating a corpus of Dutch social media posts with fine-grained cyberbullying-related text categories is an important step in addressing this issue. Being able to identify specific types of cyberbullying behavior, such as insults and threats, can help in the development of targeted prevention and intervention strategies. Furthermore, the identification of specific participants in cyberbullying conversations, such as the harasser, victim, or bystander, can enhance the analysis of human interactions and provide valuable insights into the factors that contribute to this behavior. By understanding these dynamics, researchers can develop more effective prevention and intervention strategies to combat cyberbullying.