Abstract
The wide diffusion of Online Social Networks (OSNs) presents several advantages, like the definition of simple tools for information sharing and spreading. However, OSNs present also some drawbacks, one of the most important one is the problem of privacy disclosures. Distributed Online Social Networks (DOSNs), which decentralize the control of the social network, have been recently proposed to overcome these issues. The decentralization of the control has issued several challenges, one of the main ones is guaranteeing data availability without relying on a central server. To define users’ data allocation strategies, the knowledge of the structure of the ego network and of the user’ temporal behaviour is required. Unfortunately, the lack of real datasets limits the research in this field. The goal of this paper is the study of the behaviour of users in a real social network in order to define proper strategies to allocate the users’ data on the DOSN nodes. In particular, we present an analysis of the temporal affinity and of the social communities based on a real Facebook dataset.
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This work has been funded by the project Big Data, Social Mining and Risk Management (PRA_2016_15), University of Pisa.
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De Salve, A., Guidi, B., Ricci, L. (2017). An Analysis of Ego Network Communities and Temporal a Affinity for Online Social Networks. In: Gaggi, O., Manzoni, P., Palazzi, C., Bujari, A., Marquez-Barja, J. (eds) Smart Objects and Technologies for Social Good. GOODTECHS 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 195. Springer, Cham. https://doi.org/10.1007/978-3-319-61949-1_15
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DOI: https://doi.org/10.1007/978-3-319-61949-1_15
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