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Analysis of Proximity Informed User Behavior in a Global Online Social Network

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  • Nils Breitmar
  • Matthew C. Harding
  • Hanqiao Zhang

Abstract

Despite the earlier claim of "Death of Distance", recent studies revealed that geographical proximity still greatly influences link formation in online social networks. However, it is unclear how physical distances are intertwined with users' online behaviors in a virtual world. We study the role of spatial dependence on a global online social network with a dyadic Logit model. Results show country-specific patterns for distance effect on probabilities to build connections. Effects are stronger when the possibility for two people to meet in person exists. Relative to weak ties, dependence on proximity is looser for strong social ties.

Suggested Citation

  • Nils Breitmar & Matthew C. Harding & Hanqiao Zhang, 2024. "Analysis of Proximity Informed User Behavior in a Global Online Social Network," Papers 2404.18979, arXiv.org.
  • Handle: RePEc:arx:papers:2404.18979
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    1. Portes, Richard & Rey, Helene, 2005. "The determinants of cross-border equity flows," Journal of International Economics, Elsevier, vol. 65(2), pages 269-296, March.
    2. Andrew P. Owsiak & John A. Vasquez, 2021. "Peaceful dyads: A territorial perspective," International Interactions, Taylor & Francis Journals, vol. 47(6), pages 1040-1068, November.
    3. Koen Jochmans, 2018. "Semiparametric Analysis of Network Formation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 705-713, October.
    4. Áureo de Paula, 2020. "Econometric Models of Network Formation," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 775-799, August.
    5. Bryan S. Graham, 2017. "An econometric model of network formation with degree heterogeneity," CeMMAP working papers 08/17, Institute for Fiscal Studies.
    6. Bryan S. Graham, 2017. "An Econometric Model of Network Formation With Degree Heterogeneity," Econometrica, Econometric Society, vol. 85, pages 1033-1063, July.
    7. Karyne B. Charbonneau, 2017. "Multiple fixed effects in binary response panel data models," Econometrics Journal, Royal Economic Society, vol. 20(3), pages 1-13, October.
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