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Seed Selection for Information Cascade in Multilayer Networks

  • Fredrik Erlandsson
  • Piotr Bródka
  • Anton Borg
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 689)

Abstract

Information spreading is an interesting field in the domain of online social media. In this work, we are investigating how well different seed selection strategies affect the spreading processes simulated using independent cascade model on eighteen multilayer social networks. Fifteen networks are built based on the user interaction data extracted from Facebook public pages and tree of them are multilayer networks downloaded from public repository (two of them being Twitter networks). The results indicate that various state of the art seed selection strategies for single-layer networks like K-Shell or VoteRank do not perform so well on multilayer networks and are outperformed by Degree Centrality.

Notes

Acknowledgement

This work was partially supported by The Polish National Science Centre, the decision no. DEC-2016/21/D/ST6/02408; the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 691152 (RENOIR) and the Polish Ministry of Science and Higher Education fund for supporting internationally co-financed projects in 2016–2019 (agreement no. 3628/H2020/2016/2).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringBlekinge Institute of TechnologyBlekingeSweden
  2. 2.Department of Computational IntelligenceWrocław University of Science and TechnologyWrocławPoland

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