Abstract

Information diffusion is a classical problem in social network analysis, which has been largely investigated with reference to single social networks. However, the current scenario is multi-social-network. Here, many social networks coexist and are strictly connected to each other, thanks to those users who join more social networks, acting as bridges among them. But, what happens to information diffusion when passing from a single-social-network context to a multi-social-network scenario? In this paper, we answer this question. In particular, thanks to the definition of a framework for handling these issues and to a large set of experiments, we show that, in this context, new actors and new features play the key roles. We also identify two possible improvements of our framework, namely the management of some "activation nucleuses" (i.e., some starting-node configurations that are likely to improve information diffusion) and the management of topics concerning the information to spread. In these activities, answer set programming provided us with a powerful and flexible tool for an easy setup and implementation of our investigation.

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