POLYPHONET: An advanced social network extraction system from the Web

Yutaka Matsuo*, Junichiro Mori, Masahiro Hamasaki, Takuichi Nishimura, Hideaki Takeda, Koiti Hasida, Mitsuru Ishizuka

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

99 Citations (Scopus)


Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We propose a social network extraction system called POLYPHONET, which employs several advanced techniques to extract relations of persons, to detect groups of persons, and to obtain keywords for a person. Search engines, especially Google, are used to measure co-occurrence of information and obtain Web documents. Several studies have used search engines to extract social networks from the Web, but our research advances the following points: first, we reduce the related methods into simple pseudocodes using Google so that we can build up integrated systems. Second, we develop several new algorithms for social network mining such as those to classify relations into categories, to make extraction scalable, and to obtain and utilize person-to-word relations. Third, every module is implemented in POLYPHONET, which has been used at four academic conferences, each with more than 500 participants. We overview that system. Finally, a novel architecture called Iterative Social Network Mining is proposed. It utilizes simple modules using Google and is characterized by scalability and relate-identify processes: identification of each entity and extraction of relations are repeated to obtain a more precise social network.

Original languageEnglish
Pages (from-to)262-278
Number of pages17
JournalWeb Semantics
Issue number4
Publication statusPublished - 2007 Dec
Externally publishedYes


  • Search engine
  • Social network
  • Web mining

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications


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