Information and friend segregation for online social networks: A user study

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Ahmed, Javed
Villata, Serena
Governatori, Guido
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2019
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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

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