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Exploring Regional Variations in “Socio-Spatial” Interaction and Geographic Homophily Using Location-Sharing Services Data

  • Laurie A. SchintlerEmail author
  • Rajendra Kulkarni
  • Kingsley Haynes
  • Roger Stough
Chapter
  • 21 Downloads

Abstract

This chapter examines how and to what extent there are variations in sub-regional patterns of socio-spatial interaction using a novel methodology. The methodology uses bipartite network modeling combined with spatial statistical and geographically weighted regression analysis. It provides a statistically robust approach for studying regional variations in the relationship between social and spatial interaction at different distance thresholds. The study applies the methods to the Atlanta metropolitan area using a sample of location-sharing services data. While intended as an exploratory analysis, it does provide some evidence that the association between socialization and location behavior and related distance-decay effects are not uniform in space.

References

  1. Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. arXiv.org Physics, arXiv: 0803.0476.Google Scholar
  2. Brown, C., Nicosia, V., Scellato, S., Noulas, A., & Mascolo, C. (2012a). The importance of Being placefriends: Discovering location-focused online communities. WOSN ’12, August 17, 2012, Helsinki, Finland.Google Scholar
  3. Brown, C., Nicosia, V., Scellato, S., Noulas, A., & Mascolo, C. (2012b, May). Where online friends meet: Social communities in location-based networks. In Sixth International AAAI Conference on Weblogs and Social Media.Google Scholar
  4. Cho, E., Myers, S. A., & Leskovec, J. (2011). Friendship and mobility: User movement in location-based social networks. In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). San Diego, California, USA.Google Scholar
  5. Davis, A., & Gardner, B. D. (1941). Deep South. Chicago: The University of Chicago Press.Google Scholar
  6. Elwood, S., Goodchild, F. G., & Sui, D. Z. (2011). Researching Volunteered geographic information: Spatial data, geographic research, and new social practice. Annals of the Association of American Geographers, 102(3), 571–590.Google Scholar
  7. Expert, P., Evans, T. S., Blondel, V. D., & Lambiotte, R. (2011). Uncovering space-independent communities in spatial networks. Proceedings of the National Academy of Sciences, 108(19), 7663–7668.Google Scholar
  8. Fortunato, S. (2009). Community detection in graphs. arXiv: 0906.0612 [physics.soc-ph].Google Scholar
  9. Fotheringham, A. S., Charlton, M., & Brunsdon, C. (1997a). Measuring spatial variations in relationships with geographically weighted regression. In: M. M. Fischer & A. Getis, (Eds.) Recent developments in spatial analysis (pp. 60–82). London: Springer-Verlag.Google Scholar
  10. Fotheringham, A. S., Charlton, M., & Brunsdon, C. (1997b). Two techniques for exploring non-stationarity in geographical data. Geographical Systems 4, 59–82.Google Scholar
  11. Freeman, L., & Duqueene, V. (1993). A note on colorings of two mode data. Social Networks, 15, 437–441.Google Scholar
  12. Kaltenbrunner, A., Scellato, S., Volkovich, Y., Laniodo, D., Currie, D., Julemar, E. J., & Mascolo, C. (2011). Far from the eyes, close on the web: Impact of geographic distance on online social interactions. WOSN’12, August 17, 2012, Helsinki, Finland.Google Scholar
  13. Lawlor, A., Coffey, C., McGrath, R., & Pozdnoukhov, A. (2012). Stratification structure of urban habitats. Working paper, National Centre for Geocomputation, National University of Ireland Maynooth.Google Scholar
  14. McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology 27, 415–444.Google Scholar
  15. Onnela, J.-P., Arbesman, S., González, M. C., Barabási, A.-L., & Christakis, N. A. (2011). Geographic constraints on social network groups. PLoS ONE 6(4), e16939.  https://doi.org/10.1371/journal.pone.0016939.
  16. Pelechrinis, K., & Krishnamurthy, P. (2016). Socio-spatial affiliation networks. Computer Communications, 73, 251–262.Google Scholar
  17. Takheteyev, Y., Gruzd, A., & Wellman, B. (2012). Geography of Twitter networks. Social Networks 34, 73–81.Google Scholar
  18. Volkovich, Y., Scallato, S., Laniado, D., Mascolo, C., & Kaltenbrunner, A. (2012). The length of bridge ties: Structural and geographic properties of online social interactions. Association for the Advancement of Artificial Intelligence (www.aaai.org).
  19. Walsh, F., & Pozdnoukhov, A. (2011). Spatial structure and dynamics of urban communities. Working paper, National Centre for Geocomputation, National University of Ireland Maynooth.Google Scholar
  20. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge, MA: Cambridge University Press.Google Scholar
  21. Wellman, B. (1997). An electronic group is virtually a social network. Culture of the Internet, 4, 179–205.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Laurie A. Schintler
    • 1
    Email author
  • Rajendra Kulkarni
    • 1
  • Kingsley Haynes
    • 1
  • Roger Stough
    • 1
  1. 1.The Schar School of Policy and GovernmentGeorge Mason UniversityFairfaxUSA

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