• DocumentCode
    3130495
  • Title

    Privacy settings from contextual attributes: A case study using Google Buzz

  • Author

    Mashima, Daisuke ; Shi, Elaine ; Chow, Richard ; Sarkar, Prateek ; Li, Chris ; Song, Dawn

  • Author_Institution
    Georgia Inst. of Technol., Atlanta, GA, USA
  • fYear
    2011
  • fDate
    21-25 March 2011
  • Firstpage
    257
  • Lastpage
    262
  • Abstract
    Social networks provide users with privacy settings to control what information is shared with connections and other users. In this paper, we analyze factors influencing changes in privacy-related settings in the Google Buzz social network. Specifically, we show statistics on contextual data related to privacy settings that are derived from crawled datasets and analyze the characteristics of users who changed their privacy settings. We also investigate potential neighboring effects among such users.
  • Keywords
    data privacy; social networking (online); statistics; Google Buzz; contextual attributes; privacy settings; social networks; statistics; Data privacy; Facebook; Google; Privacy; Switches; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing and Communications Workshops (PERCOM Workshops), 2011 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    978-1-61284-938-6
  • Electronic_ISBN
    978-1-61284-936-2
  • Type

    conf

  • DOI
    10.1109/PERCOMW.2011.5766879
  • Filename
    5766879