Mining the network value of customers
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SybilGuard: defending against sybil attacks via social networks
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Predicting tie strength with social media
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On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
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The growing omnipresence of the Social Web and the increasingly number of services in the Cloud have created a favourable atmosphere to develop socially-enhanced services, that is, services which are aware of the social dimension of the users to improve their experience in the Cloud. This paper introduces a model and an architecture for socially-enhanced services by mining interaction information across different Social Web sites. Most of the existing social applications require knowing who are the users socially-linked to each individual by exploring topological connections in social networks or, even, calculating the interactions network that underlies social sites. However these approaches are, on the one hand, hardly scalable when the number of users grows in the interaction network and, on the other hand, tightly coupled to the social application and so hardly reusable. The key contribution of this paper is a user-centred model whose goal is not to infer the aforementioned interaction network, but to build users' social spheres. That is, assessing the strength and the context of the user's ties by using signs of interaction available from social sites APIs (private messages, retweets, mentions,...) with user's permission. To this aim, contrary to previous approaches, we take into account (i) different interaction types and contexts, (ii) the time in which interactions occur, (iii) the people involved in them and (iv) the interactions rhythms with the rest of user's contacts. A prototype of this service has been implemented in order to, not only validate the tie strength model, but also to deploy some pilot experiences.