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