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The gravitational law of social interaction

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  • Levy, Moshe
  • Goldenberg, Jacob

Abstract

While a great deal is known about the topology of social networks, there is much less agreement about the geographical structure of these networks. The fundamental question in this context is: how does the probability of a social link between two individuals depend on the physical distance between them? While it is clear that the probability decreases with the distance, various studies have found different functional forms for this dependence. The exact form of the distance dependence has crucial implications for network searchability and dynamics: Kleinberg (2000) [15] shows that the small-world property holds if the probability of a social link is a power-law function of the distance with power −2, but not with any other power. We investigate the distance dependence of link probability empirically by analyzing four very different sets of data: Facebook links, data from the electronic version of the Small-World experiment, email messages, and data from detailed personal interviews. All four datasets reveal the same empirical regularity: the probability of a social link is proportional to the inverse of the square of the distance between the two individuals, analogously to the distance dependence of the gravitational force. Thus, it seems that social networks spontaneously converge to the exact unique distance dependence that ensures the Small-World property.

Suggested Citation

  • Levy, Moshe & Goldenberg, Jacob, 2014. "The gravitational law of social interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 418-426.
  • Handle: RePEc:eee:phsmap:v:393:y:2014:i:c:p:418-426
    DOI: 10.1016/j.physa.2013.08.067
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    References listed on IDEAS

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    Cited by:

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    3. Abraham, Samira S. & Lanzara, Gianandrea & Lazzaroni, Sara & Masella, Paolo & Squicciarini, Mara P., 2024. "Spatial and historical drivers of fake news diffusion: Evidence from anti-Muslim discrimination in India," Journal of Urban Economics, Elsevier, vol. 141(C).
    4. Augeraud Veron, E. & Marhuenda, F. & Picard, P.M., 2021. "Local social interaction and urban equilibria," Mathematical Social Sciences, Elsevier, vol. 112(C), pages 72-83.
    5. Xavier Gabaix, 2016. "Power Laws in Economics: An Introduction," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 185-206, Winter.
    6. Feifei Tan & Zhaohua Lu, 2019. "Regional sustainability system as ecosystem: case study of China’s two leading economic circles from a keystone perspective," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(2), pages 961-983, April.
    7. Wahid-Ul-Ashraf, Akanda & Budka, Marcin & Musial, Katarzyna, 2019. "How to predict social relationships — Physics-inspired approach to link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1110-1129.

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