Towards an NLP-based topic characterization of social relations

Jan Hauffa, Tobias Lichtenberg, Georg Groh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

The unstructured text content of online communication artifacts is a salient source of information about social relationships. We investigate the utility of keywords extracted from the message body as a representation of the relationship's characteristics, which are reflected by the conversation topics to a certain extent. Keyword extraction is performed using standard natural language processing methods. Communication data and human assessments of the extracted keywords are obtained from Facebook users via a custom application. The overall positive quality assessment provides evidence that the keywords indeed convey relevant information about the relationship. This kind of representation may be of value for various computational tasks from the domain of social computing.

Original languageEnglish
Title of host publicationProceedings of the 2012 ASE International Conference on Social Informatics, SocialInformatics 2012
PublisherIEEE Computer Society
Pages289-294
Number of pages6
ISBN (Print)9780769550152
DOIs
StatePublished - 2012
Event2012 ASE International Conference on Social Informatics, SocialInformatics 2012 - Washington, D.C., United States
Duration: 14 Dec 201216 Dec 2012

Publication series

NameProceedings of the 2012 ASE International Conference on Social Informatics, SocialInformatics 2012

Conference

Conference2012 ASE International Conference on Social Informatics, SocialInformatics 2012
Country/TerritoryUnited States
CityWashington, D.C.
Period14/12/1216/12/12

Keywords

  • NLP
  • keyword extraction
  • social networks
  • social relations

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