• DocumentCode
    1976614
  • Title

    Blind Spots: Unveiling users´ true willingness in online social networks

  • Author

    Di Wang ; Xinxin Liu ; Xiaolin Li

  • Author_Institution
    Scalable Software Syst. Lab., Univ. of Florida, Gainesville, FL, USA
  • fYear
    2012
  • fDate
    3-7 Dec. 2012
  • Firstpage
    2066
  • Lastpage
    2071
  • Abstract
    Although online social networks reflect real world social relationships, in many cases, online data is too scarce or implicit to reveal a user´s true willingness. This causes the Blind Spot problem in socially-rendered willingness inference systems. Blind spots are the undervalued online contacts in willingness inference because of insufficient explicit evidences. To the best of our knowledge, this is the first time to introduce and address the blind spot problem. In this paper, we propose a scheme to detect blind spots, by contradicting explicit evidences and implicit inferences. The proposed scheme uses interaction history as the explicit evidence, and social circles for implicit inference. Real world experiments and surveys demonstrate that our scheme can detect blind spots.
  • Keywords
    inference mechanisms; social networking (online); user interfaces; blind spot problem; explicit evidence; implicit inference; online contact; online social network; social relationship; socially-rendered willingness inference system; user true willingness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Communications Conference (GLOBECOM), 2012 IEEE
  • Conference_Location
    Anaheim, CA
  • ISSN
    1930-529X
  • Print_ISBN
    978-1-4673-0920-2
  • Electronic_ISBN
    1930-529X
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2012.6503420
  • Filename
    6503420