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Information diffusion in a multi-social-network scenario: framework and ASP-based analysis

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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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Notes

  1. Answer sets are supported models [51].

  2. We recall that the Jaccard coefficient J(A, B) between two sets A and B is defined as \(J(A,B)\,=\,\frac{|A \cap B|}{|A \cup B|}\).

  3. The minimum coverage value of 5 % had to be reached for each of the covered social networks.

  4. Given the values for I and Th adopted in the tests, we specialized the general encoding to one executable by DLV, which currently does not support recursive aggregates.

  5. Specifically the one requiring to cover three social networks with at least 20 % of nodes per network.

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Acknowledgments

We thank anonymous reviewers for their very useful comments and suggestions. This work was partially funded by Regione Calabria through the project Cross-channel Commerce (POR CALABRIA FESR 2007/2013 (CCI N 2007 IT 161 PO 008)), and by the project BA2Know (Business Analytics to Know) funded by the Italian Ministry of Education, University and Research.

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  1. Engineering Tributi SpA, Trento, Italy

    Giuseppe Marra

  2. Domenico Ursino, DIIES, University Mediterranea of Reggio Calabria, Via Graziella, Località Feo di Vito, 89122, Reggio Calabria, Italy

    Domenico Ursino

  3. DeMaCs, University of Calabria, Rende, CS, Italy

    Francesco Ricca & Giorgio Terracina

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  1. Giuseppe Marra
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Correspondence to Domenico Ursino.

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Marra, G., Ursino, D., Ricca, F. et al. Information diffusion in a multi-social-network scenario: framework and ASP-based analysis. Knowl Inf Syst 48, 619–648 (2016). https://doi.org/10.1007/s10115-015-0890-z

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