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Learning with multi-resolution overlapping communities

Journal Article


Abstract


  • A recent surge of participatory web and social media has created a new laboratory for studying human relations and collective behavior on an unprecedented scale. In this work, we study the predictive power of social connections to determine the preferences or behaviors of individuals such as whether a user supports a certain political view, whether one likes a product, whether she would like to vote for a presidential candidate, etc. Since an actor is likely to participate in multiple different communities with each regulating the actor’s behavior in varying degrees, and a natural hierarchy might exist between these communities, we propose to zoom into a network at multiple different resolutions and determine which communities reflect a targeted behavior. We develop an efficient algorithm to extract a hierarchy of overlapping communities. Empirical results on social media networks demonstrate the promising potential of the proposed approach in real-world applications.

Authors


  •   Wang, Xufei (external author)
  •   Tang, Lei (external author)
  •   Liu, Huan (external author)
  •   Wang, Lei

Publication Date


  • 2013

Citation


  • Wang, X., Tang, L., Liu, H. & Wang, L. (2013). Learning with multi-resolution overlapping communities. Knowledge and Information Systems, 36 (2), 517-535.

Scopus Eid


  • 2-s2.0-84880055106

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1513

Has Global Citation Frequency


Number Of Pages


  • 18

Start Page


  • 517

End Page


  • 535

Volume


  • 36

Issue


  • 2

Place Of Publication


  • United Kingdom

Abstract


  • A recent surge of participatory web and social media has created a new laboratory for studying human relations and collective behavior on an unprecedented scale. In this work, we study the predictive power of social connections to determine the preferences or behaviors of individuals such as whether a user supports a certain political view, whether one likes a product, whether she would like to vote for a presidential candidate, etc. Since an actor is likely to participate in multiple different communities with each regulating the actor’s behavior in varying degrees, and a natural hierarchy might exist between these communities, we propose to zoom into a network at multiple different resolutions and determine which communities reflect a targeted behavior. We develop an efficient algorithm to extract a hierarchy of overlapping communities. Empirical results on social media networks demonstrate the promising potential of the proposed approach in real-world applications.

Authors


  •   Wang, Xufei (external author)
  •   Tang, Lei (external author)
  •   Liu, Huan (external author)
  •   Wang, Lei

Publication Date


  • 2013

Citation


  • Wang, X., Tang, L., Liu, H. & Wang, L. (2013). Learning with multi-resolution overlapping communities. Knowledge and Information Systems, 36 (2), 517-535.

Scopus Eid


  • 2-s2.0-84880055106

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1513

Has Global Citation Frequency


Number Of Pages


  • 18

Start Page


  • 517

End Page


  • 535

Volume


  • 36

Issue


  • 2

Place Of Publication


  • United Kingdom