Information and friend segregation for online social networks: A user study
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Villata, Serena
Governatori, Guido
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Abstract
Online social networks (OSNs) captured the attention of the masses by offering attractive means of sharing personal information and developing social relationships. People expose personal information about their lives on OSNs. This may result in undesirable consequences of users’ personal information leakage to an unwanted audience and raises privacy concerns. The issue of privacy has received a significant attention in both the research literature and the mainstream media. In this paper, we present results of an empirical study that measure users’ attitude towards interpersonal privacy concerns in OSNs. The results demonstrated a serious mismatch between privacy concerns of users and their information sharing behavior. In addition, it indicated that strangers are part of user social circles, this makes privacy protection more complicated, and introduce an insider threat, whereas all existing privacy tools allow users to manage the outsider threat. Information and friend segregation strategies are suggested on the basis of user information disclosure and interaction pattern. We conclude that sensitivity of information and frequency of interaction, both, play a vital role in information and friend segregation.
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AI & Society
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34
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4
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© 2019 Springer London. This is an electronic version of an article published in AI & Society, 2019, 34 (4), pp. 753-766. AI & Society is available online at: http://link.springer.com// with the open URL of your article.
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Subject
Artificial intelligence
Cognitive and computational psychology
Philosophy
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science
Online social networks
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Ahmed, J; Villata, S; Governatori, G, Information and friend segregation for online social networks: A user study, AI & Society, 2019, 34 (4), pp. 753-766