Improving cyberbullying detection with user context

M. Dadvar; Rudolf Berend Trieschnigg; Roeland J.F. Ordelman; Franciska M.G. de Jong

doi:10.1007/978-3-642-36973-5_62

Improving cyberbullying detection with user context

M. Dadvar, Rudolf Berend Trieschnigg, Roeland J.F. Ordelman, Franciska M.G. de Jong

Databases (Former)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

247 Citations (Scopus)

314 Downloads (Pure)

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.

Original language	Undefined
Title of host publication	Proceedings of the 35th European Conference on IR Research, ECIR 2013
Place of Publication	Berlin
Publisher	Springer
Pages	693-696
Number of pages	4
ISBN (Print)	978-3-642-36972-8
DOIs	https://doi.org/10.1007/978-3-642-36973-5_62
Publication status	Published - Mar 2013
Event	35th European Conference on Information Retrieval, ECIR 2013: (IR Resarch) - Moscow, Russian Federation Duration: 24 Mar 2013 → 27 Mar 2013 Conference number: 35

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	7814
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	35th European Conference on Information Retrieval, ECIR 2013
Abbreviated title	ECIR
Country/Territory	Russian Federation
City	Moscow
Period	24/03/13 → 27/03/13

Keywords

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

Access to Document

10.1007/978-3-642-36973-5_62

Cite this

@inproceedings{36e66c8fd9b64e938331915f1638dd6d,

title = "Improving cyberbullying detection with user context",

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{\textquoteright} 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",

author = "M. Dadvar and Trieschnigg, {Rudolf Berend} and Ordelman, {Roeland J.F.} and {de Jong}, {Franciska M.G.}",

note = "10.1007/978-3-642-36973-5_62 ; 35th European Conference on Information Retrieval, ECIR 2013 ; Conference date: 24-03-2013 Through 27-03-2013",

year = "2013",

month = mar,

doi = "10.1007/978-3-642-36973-5_62",

language = "Undefined",

isbn = "978-3-642-36972-8",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "693--696",

booktitle = "Proceedings of the 35th European Conference on IR Research, ECIR 2013",

}

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, Berlin, pp. 693-696, 35th European Conference on Information Retrieval, ECIR 2013, Moscow, Russian Federation, 24/03/13. https://doi.org/10.1007/978-3-642-36973-5_62

Improving cyberbullying detection with user context. / Dadvar, M.; Trieschnigg, Rudolf Berend ; Ordelman, Roeland J.F. et al.
Proceedings of the 35th European Conference on IR Research, ECIR 2013. Berlin: Springer, 2013. p. 693-696 (Lecture Notes in Computer Science; Vol. 7814).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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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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