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Sampling Emerging Social Behavior in Facebook Using Random Walk Models

  • C. A. Piña-García
  • Dongbing Gu
Chapter
Part of the Intelligent Systems Reference Library book series (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.

Keywords

Brownian Motion Movement Path Random Walk Model Social Explorer Correlate Random Walk 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

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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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK

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