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
Link To Document :
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