Improving cyberbullying detection with user context

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

  • 36 Citations

Abstract

The negative consequences of cyberbullying are becoming more alarming every day and technical solutions that allow for taking appropriate action by means of automated detection are still very limited. Up until now, studies on cyberbullying detection have focused on individual comments only, disregarding context such as users’ characteristics and profile information. In this paper we show that taking user context into account improves the detection of cyberbullying.
LanguageUndefined
Title of host publicationProceedings of the 35th European Conference on IR Research, ECIR 2013
Place of PublicationBerlin
PublisherSpringer Verlag
Pages693-696
Number of pages4
ISBN (Print)978-3-642-36972-8
DOIs
StatePublished - Mar 2013
Event35th European Conference on Information Retrieval, ECIR 2013 - Moscow, Russian Federation
Duration: 24 Mar 201327 Mar 2013
Conference number: 35

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume7814
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference35th European Conference on Information Retrieval, ECIR 2013
Abbreviated titleECIR
CountryRussian Federation
CityMoscow
Period24/03/1327/03/13

Keywords

  • EWI-23141
  • METIS-296338
  • Cyberbullying Detection
  • Harassment Detection
  • IR-85503
  • Sentiment Analysis

Cite this

Dadvar, M., Trieschnigg, R. B., Ordelman, R. J. F., & de Jong, F. M. G. (2013). Improving cyberbullying detection with user context. In Proceedings of the 35th European Conference on IR Research, ECIR 2013 (pp. 693-696). (Lecture Notes in Computer Science; Vol. 7814). Berlin: Springer Verlag. DOI: 10.1007/978-3-642-36973-5_62
Dadvar, M. ; Trieschnigg, Rudolf Berend ; Ordelman, Roeland J.F. ; de Jong, Franciska M.G./ Improving cyberbullying detection with user context. Proceedings of the 35th European Conference on IR Research, ECIR 2013. Berlin : Springer Verlag, 2013. pp. 693-696 (Lecture Notes in Computer Science).
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abstract = "The negative consequences of cyberbullying are becoming more alarming every day and technical solutions that allow for taking appropriate action by means of automated detection are still very limited. Up until now, studies on cyberbullying detection have focused on individual comments only, disregarding context such as users’ characteristics and profile information. In this paper we show that taking user context into account improves the detection of cyberbullying.",
keywords = "EWI-23141, METIS-296338, Cyberbullying Detection, Harassment Detection, IR-85503, Sentiment Analysis",
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Dadvar, M, Trieschnigg, RB, Ordelman, RJF & de Jong, FMG 2013, Improving cyberbullying detection with user context. in Proceedings of the 35th European Conference on IR Research, ECIR 2013. Lecture Notes in Computer Science, vol. 7814, Springer Verlag, Berlin, pp. 693-696, 35th European Conference on Information Retrieval, ECIR 2013, Moscow, Russian Federation, 24/03/13. DOI: 10.1007/978-3-642-36973-5_62

Improving cyberbullying detection with user context. / Dadvar, M.; Trieschnigg, Rudolf Berend; Ordelman, Roeland J.F.; de Jong, Franciska M.G.

Proceedings of the 35th European Conference on IR Research, ECIR 2013. Berlin : Springer Verlag, 2013. p. 693-696 (Lecture Notes in Computer Science; Vol. 7814).

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

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AB - The negative consequences of cyberbullying are becoming more alarming every day and technical solutions that allow for taking appropriate action by means of automated detection are still very limited. Up until now, studies on cyberbullying detection have focused on individual comments only, disregarding context such as users’ characteristics and profile information. In this paper we show that taking user context into account improves the detection of cyberbullying.

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Dadvar M, Trieschnigg RB, Ordelman RJF, de Jong FMG. Improving cyberbullying detection with user context. In Proceedings of the 35th European Conference on IR Research, ECIR 2013. Berlin: Springer Verlag. 2013. p. 693-696. (Lecture Notes in Computer Science). Available from, DOI: 10.1007/978-3-642-36973-5_62