Community focused social network extraction

Authors:
Masahiro Hamasaki;Yutaka Matsuo;Keisuke Ishida;Yoshiyuki Nakamura;Takuichi Nishimura;Hideaki Takeda
Affiliations:
National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan;National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan;National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan;National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan;National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan;National Institute of Informatics (NII), Tokyo, Japan
Venue:
ASWC'06 Proceedings of the First Asian conference on The Semantic Web
Year:
2006

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Abstract

A social networking service can become the basis for the information infrastructure of the future For that purpose, it is important to extract social networks that reflect actual social networks which users have already had Providing a simple means for users to register their social relations is also important We propose a method that combines various approaches to extract social networks Especially, three kinds of networks are extracted: user-registered Know-link networks; Web-mined Web-link networks; and face-to-face Touch-link networks This paper describes the combination of social network extraction for an event-participant community Analyses on the extracted social networks are also presented.