• DocumentCode
    3281809
  • Title

    A Fuzzy Approach to Social Network Analysis

  • Author

    Brunelli, Matteo ; Fedrizzi, Michele

  • Author_Institution
    Turku Centre for Comput. Sci. & IAMSR, Abo Akademi Univ. Abo, Turku, Finland
  • fYear
    2009
  • fDate
    20-22 July 2009
  • Firstpage
    225
  • Lastpage
    230
  • Abstract
    Adjacency relations for social network analysis have usually been tackled in their bidimensional form, in the sense that relations are computed over pairs of objects. Nevertheless, this paper considers the bidimensional case as restrictive and it proposes an approach where the dimension of the analysis is not limited to binary relations. With the aid of fuzzy logic and OWA operators, it is showed that the interpretation of m-ary adjacency relations is the same of binary relations and therefore they can consistently be employed in social network analysis and some novel results be derived. Besides justifying the use of m-ary relations, the paper proposes a way to characterize them and, eventually, it will provide the reader with an example section.
  • Keywords
    fuzzy logic; fuzzy set theory; social networking (online); OWA operators; fuzzy approach; fuzzy logic; m-ary adjacency relations; social network analysis; OWA operators; Social Network Analysis; adjacency relation; fuzzy sets theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
  • Conference_Location
    Athens
  • Print_ISBN
    978-0-7695-3689-7
  • Type

    conf

  • DOI
    10.1109/ASONAM.2009.72
  • Filename
    5231883