Cyberbullying is a serious social problem in online environments and social networks. Current approaches to tackle this problem are still inadequate for detecting bullying incidents or to flag bullies. In this study we used a multi-criteria evaluation system to obtain a better understanding of YouTube users‟ behaviour and their characteristics through expert knowledge. Based on experts‟ knowledge, the system assigns a score to the users, which represents their level of “bulliness‿ based on the history of their activities, The scores can be used to discriminate among users with a bullying history and those who were not engaged in hurtful acts. This preventive approach can provide information about users of social networks and can be used to build monitoring tools to aid finding and stopping potential bullies.
|Title of host publication||25th Benelux Conference on Artificial Intelligence, BNAIC 2013|
|Place of Publication||Delft|
|Publisher||Delft University of Technology|
|Number of pages||8|
|ISBN (Print)||not assigned|
|Publication status||Published - Nov 2013|
|Event||25th Benelux Conference on Artificial Intelligence, BNAIC 2013 - Delft University of Technology, Delft, Netherlands|
Duration: 7 Nov 2013 → 8 Nov 2013
Conference number: 25
|Conference||25th Benelux Conference on Artificial Intelligence, BNAIC 2013|
|Period||7/11/13 → 8/11/13|
- Multi-criteria evaluation system
- Sentiment Analysis
Dadvar, M., Trieschnigg, R. B., & de Jong, F. M. G. (2013). Expert knowledge for automatic detection of bullies in social networks. In 25th Benelux Conference on Artificial Intelligence, BNAIC 2013 (pp. 57-64). Delft: Delft University of Technology.