Expert knowledge for automatic detection of bullies in social networks

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Abstract

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.
Original languageUndefined
Title of host publication25th Benelux Conference on Artificial Intelligence, BNAIC 2013
Place of PublicationDelft
PublisherDelft University of Technology
Pages57-64
Number of pages8
ISBN (Print)not assigned
Publication statusPublished - Nov 2013
Event25th Benelux Conference on Artificial Intelligence, BNAIC 2013 - Delft University of Technology, Delft, Netherlands
Duration: 7 Nov 20138 Nov 2013
Conference number: 25

Publication series

Name
PublisherTU Delft

Conference

Conference25th Benelux Conference on Artificial Intelligence, BNAIC 2013
Abbreviated titleBNAIC
CountryNetherlands
CityDelft
Period7/11/138/11/13

Keywords

  • EWI-23856
  • Multi-criteria evaluation system
  • METIS-300101
  • IR-88358
  • Cyberbullying
  • Sentiment Analysis

Cite this

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.