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Entangling Mobility and Interactions in Social Media

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  • Przemyslaw A Grabowicz
  • José J Ramasco
  • Bruno Gonçalves
  • Víctor M Eguíluz

Abstract

Daily interactions naturally define social circles. Individuals tend to be friends with the people they spend time with and they choose to spend time with their friends, inextricably entangling physical location and social relationships. As a result, it is possible to predict not only someone’s location from their friends’ locations but also friendship from spatial and temporal co-occurrence. While several models have been developed to separately describe mobility and the evolution of social networks, there is a lack of studies coupling social interactions and mobility. In this work, we introduce a model that bridges this gap by explicitly considering the feedback of mobility on the formation of social ties. Data coming from three online social networks (Twitter, Gowalla and Brightkite) is used for validation. Our model reproduces various topological and physical properties of the networks not captured by models uncoupling mobility and social interactions such as: i) the total size of the connected components, ii) the distance distribution between connected users, iii) the dependence of the reciprocity on the distance, iv) the variation of the social overlap and the clustering with the distance. Besides numerical simulations, a mean-field approach is also used to study analytically the main statistical features of the networks generated by a simplified version of our model. The robustness of the results to changes in the model parameters is explored, finding that a balance between friend visits and long-range random connections is essential to reproduce the geographical features of the empirical networks.

Suggested Citation

  • Przemyslaw A Grabowicz & José J Ramasco & Bruno Gonçalves & Víctor M Eguíluz, 2014. "Entangling Mobility and Interactions in Social Media," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-12, March.
  • Handle: RePEc:plo:pone00:0092196
    DOI: 10.1371/journal.pone.0092196
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    References listed on IDEAS

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    1. Lambiotte, Renaud & Blondel, Vincent D. & de Kerchove, Cristobald & Huens, Etienne & Prieur, Christophe & Smoreda, Zbigniew & Van Dooren, Paul, 2008. "Geographical dispersal of mobile communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5317-5325.
    2. Przemyslaw A Grabowicz & José J Ramasco & Esteban Moro & Josep M Pujol & Victor M Eguiluz, 2012. "Social Features of Online Networks: The Strength of Intermediary Ties in Online Social Media," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-9, January.
    3. Filippo Simini & Marta C. González & Amos Maritan & Albert-László Barabási, 2012. "A universal model for mobility and migration patterns," Nature, Nature, vol. 484(7392), pages 96-100, April.
    4. Santi Phithakkitnukoon & Zbigniew Smoreda & Patrick Olivier, 2012. "Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-9, June.
    5. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
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    1. Zexun Chen & Sean Kelty & Alexandre G. Evsukoff & Brooke Foucault Welles & James Bagrow & Ronaldo Menezes & Gourab Ghoshal, 2022. "Contrasting social and non-social sources of predictability in human mobility," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

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