Detecting offensive language in social media to protect adolescent online safety

Ying Chen, Yilu Zhou, Sencun Zhu, Heng Xu

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

216 Scopus citations

Abstract

Since the textual contents on online social media are highly unstructured, informal, and often misspelled, existing research on message-level offensive language detection cannot accurately detect offensive content. Meanwhile, user-level offensiveness detection seems a more feasible approach but it is an under researched area. To bridge this gap, we propose the Lexical Syntactic Feature (LSF) architecture to detect offensive content and identify potential offensive users in social media. We distinguish the contribution of pejoratives/profanities and obscenities in determining offensive content, and introduce hand-authoring syntactic rules in identifying name-calling harassments. In particular, we incorporate a user's writing style, structure and specific cyber bullying content as features to predict the user's potentiality to send out offensive content. Results from experiments showed that our LSF framework performed significantly better than existing methods in offensive content detection. It achieves precision of 98.24% and recall of 94.34% in sentence offensive detection, as well as precision of 77.9% and recall of 77.8% in user offensive detection. Meanwhile, the processing speed of LSF is approximately 10msec per sentence, suggesting the potential for effective deployment in social media.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012
Pages71-80
Number of pages10
DOIs
StatePublished - 2012
Event2012 ASE/IEEE International Conference on Social Computing, SocialCom 2012 and the 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2012 - Amsterdam, Netherlands
Duration: Sep 3 2012Sep 5 2012

Publication series

NameProceedings - 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012

Other

Other2012 ASE/IEEE International Conference on Social Computing, SocialCom 2012 and the 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2012
CountryNetherlands
CityAmsterdam
Period9/3/129/5/12

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality

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