From Causal History to Social Network in Distributed Social Semantic Software

Khaled Aslan 1 Hala Skaf-Molli 1 Pascal Molli 1
1 SCORE - Services and Cooperation
Inria Nancy - Grand Est, LORIA - NSS - Department of Networks, Systems and Services
Abstract : Web 2.0 raises the importance of collaboration powered by social software. Social software clearly illustrated how it is possible to convert a community of strangers into a community of collaborators producing all together valuable content. However, collaboration is currently supported by collaboration providers such as Google, Yahoo, etc. following "Collaboration as a Service (CaaS)" approach. This approach arises privacy and censorship issues. Users have to trust CaaS providers for both security of hosted data and usage of collected data. Alternative approaches including private peer-to-peer networks, friend-to-friend networks, distributed version control systems, distributed peer-to-peer groupware, support collaboration without requiring a collaboration provider. Collaboration is powered with the resources provided by the users. If it is easy for a collaboration provider to extract the complete social network graph from the observed interactions. Obtaining social network informations in the distributed approach is more challenging. In fact, the distributed approach is designed to protect privacy of users and thus makes extracting the whole social network difficult. In this paper, we show how it is possible to compute a local view of the social network on each site in a distributed collaborative system approach.
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Khaled Aslan, Hala Skaf-Molli, Pascal Molli. From Causal History to Social Network in Distributed Social Semantic Software. Web Science Conference 2010 - WebSci10, Web Science Trust, Apr 2010, Raleigh, United States. ⟨inria-00461110v2⟩

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