• DocumentCode
    27072
  • Title

    Understanding Sensitivity by Analyzing Anonymity [Guest editor´s introduction]

  • Author

    Peddinti, Sai Teja ; Korolova, Aleksandra ; Bursztein, Elie ; Sampemane, Geetanjali

  • Volume
    13
  • Issue
    2
  • fYear
    2015
  • fDate
    Mar.-Apr. 2015
  • Firstpage
    14
  • Lastpage
    21
  • Abstract
    We can infer user privacy preferences and expectations by observing how people use existing product features. An analysis of how users employ anonymity features on Quora, a question-and-answer site, shows that the range of topics they consider sensitive is much broader than what service providers or regulators typically deem sensitive. A data-driven approach can help online services improve their products by developing features that let users express and exercise privacy preferences more effectively.
  • Keywords
    Internet; data privacy; Quora; data-driven approach; online services; question-and-answer site; user privacy expectations; user privacy preferences; Context modeling; Information analysis; Privacy; Product design; Search engines; Sensitivity; Social network services; Sociology; Web sites; Web technologies; data analysis; privacy; sociology;
  • fLanguage
    English
  • Journal_Title
    Security & Privacy, IEEE
  • Publisher
    ieee
  • ISSN
    1540-7993
  • Type

    jour

  • DOI
    10.1109/MSP.2015.45
  • Filename
    7085962