Abstract
Ideas, information, viruses: all of them, with their mechanisms, can spread over the complex social tissues described by our interpersonal relations. Classical spreading models can agnostically from the object of which they simulate the diffusion, thus considering spreading of virus, ideas and innovations alike. Indeed, such simplification makes easier to define a standard set of tools that can be applied to heterogeneous contexts; however, it can also lead to biased, partial, simulation outcomes. In this work we discuss the concepts of active and passive diffusion: moving from analysis of a well-known passive model, the Threshold one, we introduce two novel approaches whose aim is to provide active and mixed schemas applicable in the context of innovations/ideas diffusion simulation. Our data-driven analysis shows how, in such context, the adoption of exclusively passive/active models leads to conflicting results, thus highlighting the need of mixed approaches.
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Notes
- 1.
All the methods have been implemented by the authors and are made available within the “NDlib: Network Diffusion library”, [13] https://github.com/GiulioRossetti/ndlib.
- 2.
Pseudocode for the Profile-Threshold is not shown since it represents a combination of the two previously described approaches.
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Acknowledgments
This work is funded by the European Community’s H2020 Program under the funding scheme. “FETPROACT-1-2014: Global Systems Science (GSS)”, grant agreement # 641191 CIMPLEX “Bringing CItizens, Models and Data together in Participatory, Interactive SociaL EXploratories”(CIMPLEX: https://www.cimplex-project.eu). This work is supported by the European Community’s H2020 Program under the scheme “INFRAIA-1-2014-2015: Research Infrastructures”, grant agreement #654024 “SoBigData: Social Mining & Big Data Ecosystem”(SoBigData: http://www.sobigdata.eu)
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Milli, L., Rossetti, G., Pedreschi, D., Giannotti, F. (2018). Information Diffusion in Complex Networks: The Active/Passive Conundrum. In: Cherifi, C., Cherifi, H., Karsai, M., Musolesi, M. (eds) Complex Networks & Their Applications VI. COMPLEX NETWORKS 2017. Studies in Computational Intelligence, vol 689. Springer, Cham. https://doi.org/10.1007/978-3-319-72150-7_25
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DOI: https://doi.org/10.1007/978-3-319-72150-7_25
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