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
Link To Document