Encyclopedia of Social Network Analysis and Mining

2018 Edition
| Editors: Reda Alhajj, Jon Rokne

Modeling and Analysis of Spatiotemporal Social Networks

  • Venkata M. V. Gunturi
  • Ivan Brugere
  • Shashi Shekhar
Reference work entry
DOI: https://doi.org/10.1007/978-1-4939-7131-2_320



Dynamic social network analysis

Analysis of social networks focused on detecting changes in relationships between actors or broader changes in graph structure over time

Geo-social networking

A set of technologies which makes use of a user’s geographical position or context to provide data or enable users to publish information relevant to that context


The capacity for the characteristics of a social networking dataset such as types of interactions within the network, and spatial and temporal granularity to capture a particular social relationship


A structural group within a social network which embodies some shared characteristic with some measure of exclusivity


Spatiotemporal social networks model the relationships expressed in a social network and the changes to it over time. These...

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We are particularly grateful to the members of the Spatial Database Research Group and Dr. Karsten Steinhaeuser at the University of Minnesota for their helpful comments and valuable suggestions. We would like to thank Prof. Kathleen Carley at Carnegie Mellon University for discussion and direction. We would also like to extend our thanks to Kim Koffolt for improving the readability of this paper.


  1. Backstrom L, Sun E, Marlow C (2010) Find me if you can: improving geographical prediction with social and spatial proximity. In: Proceedings of the 19th international conference on World wide web, ACM, pp 61–70Google Scholar
  2. Bengtsson L, Lu X, Thorson A, Garfield R, von Schreeb J (2011) Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti. PLoS Med 8(8):e1001083. doi:10.1371/journal.pmed.1001083CrossRefGoogle Scholar
  3. Cheng Z, Caverlee J, Lee K (2010) You are where you tweet: a content- based approach to geo-locating twitter users. In: Proceedings of the 19th ACM international conference on Information and knowledge management, ACM, pp 759–768Google Scholar
  4. Cho E, Myers S, Leskovec J (2011). Friendship and mobility: user movement in location-based social networks. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '11), San Diego, USA. ACM pp 1082–1090Google Scholar
  5. Cohen J, Tita G (1999) Diffusion in homicide: exploring a general method for detecting spatial diffusion processes. J Quant Criminol 15(4):451–493CrossRefGoogle Scholar
  6. Eagle N, Pentland A, Lazer D (2009) Inferring friendship network structure by using mobile phone data. Proc Natl Acad Sci 106(36):15274–15278.  https://doi.org/10.1073/pnas.0900282106CrossRefGoogle Scholar
  7. Freeman LC (2004) The development of social network analysis. Empirical Press, VancouverGoogle Scholar
  8. George B, Shekhar S (2006) Time-aggregated graphs for modeling spatiotemporal networks. J Data Seman 11:191–212Google Scholar
  9. Gunturi VMV, Shekhar S, Joseph K, Carley KM (2016) Scalable computational techniques for centrality metrics on temporally detailed social network. Mach Learn:1–37.  https://doi.org/10.1007/s10994-016-5583-7
  10. Habiba H, Yu Y, Berger-Wolf T, Saia J (2008) Finding spread blockers in dynamic networks. In: Proceedings of the second international conference on Advances in social network mining and analysis, Springer, vol 8, pp 55–76CrossRefGoogle Scholar
  11. Lauw H, Lim E, Pang H, Tan T (2005) Social network discovery by mining spatio-temporal events. Comput Math Organ Theory 11(2):97–118.  https://doi.org/10.1007/s10588-005-3939-9CrossRefzbMATHGoogle Scholar
  12. Liben-Nowell D, Kleinberg J (2007) The link-prediction problem for social networks. J Am Soc Inf Sci Technol 58(7):1019–1031.  https://doi.org/10.1002/asi.20591CrossRefGoogle Scholar
  13. Liben-Nowell D, Novak J, Kumar R, Raghavan P, Tomkins A (2005) Geographic routing in social networks. Proc Natl Acad Sci 102(33):11623CrossRefGoogle Scholar
  14. Liljeros F, Edling CR, Amaral LA, Stanley HE, Aberg Y (2001) The web of human sexual contacts. Nature 411(6840):907–908CrossRefGoogle Scholar
  15. Madan A, Cebrian M, Lazer D, Pentland A (2010) Social sensing for epidemiological behavior change. In: Proceedings of the 12th ACM international conference on Ubiquitous computing, ACM, pp 291–300Google Scholar
  16. Moon I, Carley K (2007) Modeling and simulating terrorist networks in social and geospatial dimensions. Intell Syst IEEE 22(5):40–49CrossRefGoogle Scholar
  17. Newman MEJ (2004) Coauthorship networks and patterns of scientific collaboration. Proc Natl Acad Sci U S A 101(Suppl 1):5200–5205. doi:10.1073/pnas.0307545100CrossRefGoogle Scholar
  18. Onnela J, Arbesman S, Gonzalez M, Barabasi AL, Christakis N (2011) Geographic constraints on social network groups. PLoS One 6(4).  https://doi.org/10.1371/journal.pone.0016939CrossRefGoogle Scholar
  19. Pawling A, Schoenharl T, Yan P (2008) WIPER: an emergency response system. In: Proceedings of the 5th international ISCRAM Conference, May 2008Google Scholar
  20. Sakaki T, Okazaki M, Matsuo Y (2010) Earthquake shakes Twitter users: real-time event detection by social sensors. In: Proceedings of the 19th international conference on World wide web, ACM, pp 851–860Google Scholar
  21. Tang J, Musolesi M, Mascolo C, Latora V, Nicosia V (2010) Analysing information flows and key mediators through temporal centrality metrics. In: Proceedings of the 3rd workshop on social network systems, ACM, pp 1–6Google Scholar
  22. Tantipathananandh C, Berger-Wolf T, Kempe D (2007) A framework for community identification in dynamic social networks. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, pp 717–726Google Scholar
  23. Wang et al (2011). Human mobility, social ties, and link prediction. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '11), San Diego, USA. ACM pp 1100–1108Google Scholar
  24. Wasserman S, Faust K (1994) Social network analysis: methods and applications, Structural analysis in the social sciences, vol 24. Cambridge University Press, Cambridge.  https://doi.org/10.1525/ae.1997.24.1.219CrossRefzbMATHGoogle Scholar
  25. Wei W, Carley KM (2015) Measuring temporal patterns in dynamic social networks. ACM Trans Knowl Discov Data 10:1–27CrossRefGoogle Scholar
  26. Wesolowski A, Eagle N (2010) Parameterizing the dynamics of slums. In: AAAI spring symposium on artificial intelligence, June 2010Google Scholar
  27. Yang J, Leskovec J (2010) Modeling information diffusion in implicit networks. In: Proceedings of the 2010 I.E. international conference on data mining, ICDM ‘10, pp 599–608Google Scholar
  28. Zhao Q, Mitra P, Chen B (2007) Temporal and information flow based event detection from social text streams. In: Proceedings of the 22nd national conference on artificial intelligence, vol 2. AAAI Press, pp 1501–1506Google Scholar
  29. Zheng Y, Zhou X (eds) (2011) Computing with spatial trajectories. Springer, New YorkGoogle Scholar

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© Springer Science+Business Media LLC, part of Springer Nature 2018

Authors and Affiliations

  • Venkata M. V. Gunturi
    • 1
  • Ivan Brugere
    • 2
  • Shashi Shekhar
    • 3
  1. 1.IIIT-DelhiNew DelhiIndia
  2. 2.University of Illinois at ChicagoChicagoUSA
  3. 3.Department of Computer Science, University of MinnesotaMinneapolisUSA

Section editors and affiliations

  • Gao Cong
    • 1
  • Bee-Chung Chen
    • 2
  1. 1.Nanyang Technological University (NTU)SingaporeSingapore
  2. 2.Nanyang UniversitySingaporeSingapore