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Modelling Trend Progression Through an Extension of the Polya Urn Process

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Advances in Network Science (NetSci-X 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9564))

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Abstract

Knowing how and when trends are formed is a frequently visited research goal. In our work, we focus on the progression of trends through (social) networks. We use a random graph (RG) model to mimic the progression of a trend through the network. The context of the trend is not included in our model. We show that every state of the RG model maps to a state of the Polya process. We find that the limit of the component size distribution of the RG model shows power-law behaviour. These results are also supported by simulations.

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Authors and Affiliations

  1. Faculty of Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Marijn ten Thij & Sandjai Bhulai

Authors
  1. Marijn ten Thij
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  2. Sandjai Bhulai
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Corresponding author

Correspondence to Marijn ten Thij .

Editor information

Editors and Affiliations

  1. Polish-Japanese Academy, Warzaw, Poland

    Adam Wierzbicki

  2. Universität Konstanz, Konstanz, Baden-Württemberg, Germany

    Ulrik Brandes

  3. ETH Zürich, Zürich, Switzerland

    Frank Schweitzer

  4. University of Pisa, Pisa, Italy

    Dino Pedreschi

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ten Thij, M., Bhulai, S. (2016). Modelling Trend Progression Through an Extension of the Polya Urn Process. In: Wierzbicki, A., Brandes, U., Schweitzer, F., Pedreschi, D. (eds) Advances in Network Science. NetSci-X 2016. Lecture Notes in Computer Science(), vol 9564. Springer, Cham. https://doi.org/10.1007/978-3-319-28361-6_5

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  • DOI: https://doi.org/10.1007/978-3-319-28361-6_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28360-9

  • Online ISBN: 978-3-319-28361-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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