Location Privacy in Pervasive Computing
IEEE Pervasive Computing
Proceedings of the Joint JSAI 2001 Workshop on New Frontiers in Artificial Intelligence
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CHI '05 Extended Abstracts on Human Factors in Computing Systems
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CENTRIC '09 Proceedings of the 2009 Second International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies, and Services
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Privacy analysis in mobile social networks: the influential factors for disclosure of personal data
International Journal of Wireless and Mobile Computing
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Ubiquitous social networking services offer new opportunities for developing advantageous relationships by uncovering hidden connections that people share with others nearby. As sharing of personal information is an intrinsic part of ubiquitous social networking, these services are subject to crucial privacy threats. In order to contribute to the design of privacy management systems, we present results of a mixed methods study that investigated the influential factors for the variation of human data sensitivity upon different circumstances. The results indicate that the users' information sensitivity is decreasing inversely proportionally to the relevance of data disclosure for initiation of relationships with others. We suggest privacy designers should take into account the purpose of disclosure and environment as primary indexes for data disclosure. Other influential factors, i.e. activity, mood, location familiarity, number of previous encounters and mutual friends, were also discovered to influence participants' data disclosure, but as factors of secondary importance.