Title :
Understanding Sensitivity by Analyzing Anonymity [Guest editor´s introduction]
Author :
Peddinti, Sai Teja ; Korolova, Aleksandra ; Bursztein, Elie ; Sampemane, Geetanjali
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;
Journal_Title :
Security & Privacy, IEEE
DOI :
10.1109/MSP.2015.45