0000000000162187

AUTHOR

Andrea Michienzi

0000-0001-8005-8701

Exploiting community detection to recommend privacy policies in decentralized online social networks

The usage of Online Social Networks (OSNs) has become a daily activity for billions of people that share their contents and personal information with the other users. Regardless of the platform exploited to provide the OSNs’ services, these contents’ sharing could expose the OSNs’ users to a number of privacy risks if proper privacy-preserving mechanisms are not provided. Indeed, users must be able to define its own privacy policies that are exploited by the OSN to regulate access to the shared contents. To reduce such users’ privacy risks, we propose a Privacy Policies Recommended System (PPRS) that assists the users in defining their own privacy policies. Besides suggesting the most appro…

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Studying micro-communities in Facebook Communities

In the visionary view of the future Internet, named the Next Generation Internet, a current idea is to have a user-centric approach where human behavior models will be used to define the networks or to manage services. During the last years, a great trend in current Social Media platforms is to offer the opportunity to establish and join groups of people online. Despite human behaviour in current Online Social Media have been studied in depth, characteristics of these aggregations of people in content-based communities are still unknown. In this paper, we propose an evaluation of micro-communities of users inside the big network of Facebook groups to understand how and when users are active…

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