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Sampling Emerging Social Behavior in Facebook Using Random Walk Models

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Computational Models of Complex Systems

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 53))

Abstract

It has long been recognized that random walk models apply to a great diversity of situations such as: economics, mathematics and biophysics; current trends about Open Social Networks require new approaches for analyzing material publicly accessible. Thus, in this chapter we examine the potential of random walks to further our understanding about monitoring Social Behavior, taking Facebook as a case study. Although most of the work related to random walk models is traditionally used to generate animal movement paths, it is also possible to adapt classic diffusion models into exploratory algorithms with the aim to improve the ability to search under a complex environment. This algorithmic abstraction provides an analogy for a dissipative process within which trajectories are drawn through the virtual nodes of Facebook.

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Notes

  1. 1.

    Kurtosis is the degree of peakedness of a distribution. Higher kurtosis means more of the variance is the result of infrequent extreme deviations.

  2. 2.

    An extensive search consist in long steps that improve the searching efficiency by using super-diffusive phases, e.g., ballistic motion and Lévy walks.

  3. 3.

    This list of keywords was mainly suggested by public preferences and current breaking news.

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Acknowledgments

The authors thank the reviewers of this chapter for their useful comments. Mr. Piña-García has been supported by the Mexican National Council of Science and Technology (CONACYT), through the program “Becas para estudios de posgrado en el extranjero” (no. 213550).

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Authors and Affiliations

  1. School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK

    C. A. Piña-García & Dongbing Gu

Authors
  1. C. A. Piña-García
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  2. Dongbing Gu
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Correspondence to C. A. Piña-García .

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Editors and Affiliations

  1. Department of Computer Science, Troy University, Troy, Alabama, USA

    Vijay Kumar Mago

  2. The IRMACS Centre, Simon Fraser University The MoCSSy Program, Burnaby, British Columbia, Canada

    Vahid Dabbaghian

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Piña-García, C.A., Gu, D. (2014). Sampling Emerging Social Behavior in Facebook Using Random Walk Models. In: Mago, V., Dabbaghian, V. (eds) Computational Models of Complex Systems. Intelligent Systems Reference Library, vol 53. Springer, Cham. https://doi.org/10.1007/978-3-319-01285-8_12

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  • DOI: https://doi.org/10.1007/978-3-319-01285-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01284-1

  • Online ISBN: 978-3-319-01285-8

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