Towards User Modelling in the Combat against Cyberbullying
Friendships, relationships and social communications have all gone to a new level with new definitions as a result of the invention of online social networks. Meanwhile, alongside this transition there is increasing evidence that online social applications have been used by children and adolescents for bullying. State-of-the-art studies in cyberbullying detection have mainly focused on the content of the conversations while largely ignoring the users involved in cyberbullying. We hypothesis that incorporation of the users’ profile, their characteristics, and post-harassing behaviour, for instance, posting a new status in another social network as a reaction to their bullying experience, will improve the accuracy of cyberbullying detection. Cross-system analyses of the users’ behaviour - monitoring users’ reactions in different online environments - can facilitate this process and could lead to more accurate detection of cyberbullying. This paper outlines the framework for this faceted approach.
KeywordsOnline Social Network Supervise Learning Approach Online Bully Social Networking Graph Multiclass Classifier
Unable to display preview. Download preview PDF.
- 2.Espelage, D.L., Swearer, S.M.: Research on school bullying and victimization. School Psychology Review 32, 365–383 (2003)Google Scholar
- 4.Kowalski, R.M., Limber, S.P., Agatston, P.W.: Cyber bullying: Bullying in the digital age, p. 224. Blackwell Publishing (2008)Google Scholar
- 5.Yin, D., Xue, Z., Hong, L., Davison, B.D., Kontostathis, A., Edwards, L.: Detection of harassment on Web 2.0. In: Proceedings of CAW2.0, Madrid, April 20-24 (2009)Google Scholar
- 6.Dinakar, K., Reichart, R., Lieberman, H.: Modelling the Detection of Textual Cyberbullying. In: ICWSM 2011, Barcelona, Spain, July 17-21 (2011)Google Scholar
- 7.Kontostathis, A.: ChatCoder: Toward the tracking and categorization of internet predators. In: Proceedings of SDM 2009, Sparks, NV, May 2 (2009)Google Scholar
- 8.Tan, P.N., Chen, F., Jain, A.: Information assurance: Detection of web spam attacks in social media. In: Proceedings of Army Science Conference, Orland, Florida (2010)Google Scholar
- 14.Abel, F., Henze, N., Herder, E., Krause, D.: Linkage, aggregation, alignment and enrichment of public user profiles with Mypes. In: Proceedings of I-SEMANTICS, Graz, Austria, pp. 1–8 (September 2010)Google Scholar