BullyBlocker: Towards the identification of cyberbullying in social networking sites

Yasin Silva, Christopher Rich, Deborah Hall

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Cyberbullying is the deliberate use of online digital media to communicate false, embarrassing, or hostile information about another person. It is the most common online risk for adolescents and well over half of young people do not tell their parents when it occurs. While there have been many studies about the nature and prevalence of cyberbullying, there has been relatively less work in the area of automated identification of cyberbullying in social media sites. The focus of our work is to develop an automated model to identify and measure the degree of cyberbullying in social networking sites, and a Facebook app for parents, built on this model, that notifies them when cyberbullying occurs. This paper describes the challenges associated with building a computer model for cyberbullying identification, presents key results from psychology research that can be used in such a model, describes an initial model and mobile app design for cyberbullying identification, and describes key areas of future work to improve upon the initial model.

Original languageEnglish (US)
Title of host publicationProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1377-1379
Number of pages3
ISBN (Electronic)9781509028467
DOIs
StatePublished - Nov 21 2016
Event2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States
Duration: Aug 18 2016Aug 21 2016

Other

Other2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
CountryUnited States
CitySan Francisco
Period8/18/168/21/16

Keywords

  • automated identification
  • cyberbullying
  • Facebook
  • social networks

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Sociology and Political Science
  • Communication

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  • Cite this

    Silva, Y., Rich, C., & Hall, D. (2016). BullyBlocker: Towards the identification of cyberbullying in social networking sites. In Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 (pp. 1377-1379). [7752420] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASONAM.2016.7752420