• DocumentCode
    1699705
  • Title

    Predicting privacy settings with a user-centered approach

  • Author

    Watson, Jason

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Syst., Univ. of North Alabama, Florence, AL, USA
  • fYear
    2015
  • Firstpage
    499
  • Lastpage
    500
  • Abstract
    People are connecting and sharing large amounts of personal information through social media sites, cloud and health services, and other online applications. Users often manage their interactions and information disclosures on these sites using a variety of privacy settings. The use of privacy settings on social networking sites (SNS) such as Facebook has been extensively studied. Researchers have found that users have many friends and desire to selectively share with multiple audiences. However, users struggle to manage their privacy settings as they are quite complex and the structure of the settings changes frequently. As a result, users can share information more broadly than intended, even within the “friend” group, resulting in embarrassment or regret. Rather than adjust confusing privacy settings, users may resort to various coping mechanisms such as censoring their disclosures.
  • Keywords
    cloud computing; data privacy; human factors; security of data; social networking (online); Facebook; SNS; cloud computing; health services; information disclosures; online applications; personal information sharing; privacy setting prediction; social media sites; social networking sites; user-centered approach; Data privacy; Facebook; Indexes; Privacy; Security; Sensitivity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Collaboration Technologies and Systems (CTS), 2015 International Conference on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4673-7647-1
  • Type

    conf

  • DOI
    10.1109/CTS.2015.7210443
  • Filename
    7210443