Towards the detection of cyberbullying based on social network mining techniques

• Published in: 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC) pp. 1 - 2
• Main Authors: Ting, I-Hsien, Liou, Wun Sheng, Liberona, Dario, Wang, Shyue-Liang, Tarazona Bermudez, Giovanny Mauricio
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-10-2017
• Subjects: cyberbullying; Data mining; Dictionaries; Feature extraction; Focusing; Information management; Internet; social network; social network analysis; social network mining; Social network services
• DOI: 10.1109/BESC.2017.8256403

In recent years, users are widely intend to express and share their opinions over the Internet. However, due to the characters of social media, it appears negative use of social media. Cyberbullying is one of the abuse behavior in the Internet as well as a very serious social problem. Under this background and motivation, it can help to prevent the happen of cyberbullying if we can develop relevant techniques to discover cyberbullying in social media. Thus, in this paper we propose an approach based on social networks analysis and data mining for cyberbullying detection. In the approach, there are three main techniques for cyberbullying discovery will be studied, including keyword matching technique, opinion mining and social network analysis. In addition to the approach, we will also discuss the experimental design for the evaluation of the performance.