Inferring Real-World Relationships from Spatiotemporal Data

The pervasiveness of GPS-enabled mobile devices and the popularity of location-based services have generated, for the first time, massive data that represents the movements of people in the real world at a high resolution, aka spatiotemporal data. Such collections of spatiotemporal data constitute a rich source of information for studying various social behaviors, and in particular, give a boost to the study of inferring the real-world social connections from spatiotemporal data. This article surveys the prominent techniques proposed for deriving social connections and social strength from spatiotemporal data and discusses their formulations.

[1]  Nick Roussopoulos,et al.  Nearest neighbor queries , 1995, SIGMOD '95.

[2]  Cyrus Shahabi,et al.  The spatial skyline queries , 2006, VLDB.

[3]  Dan Cosley,et al.  Inferring social ties from geographic coincidences , 2010, Proceedings of the National Academy of Sciences.

[4]  Peng Wu,et al.  Close & closer: social cluster and closeness from photo collections , 2009, MM '09.

[5]  Aniket Kittur,et al.  Bridging the gap between physical location and online social networks , 2010, UbiComp.

[6]  E. Rogers,et al.  Communication of Innovations; A Cross-Cultural Approach. , 1974 .

[7]  Laks V. S. Lakshmanan,et al.  Information and Influence Propagation in Social Networks , 2013, Synthesis Lectures on Data Management.

[8]  L. Jost Entropy and diversity , 2006 .

[9]  Xing Xie,et al.  Mining user similarity based on location history , 2008, GIS '08.

[10]  David Lazer,et al.  Inferring friendship network structure by using mobile phone data , 2009, Proceedings of the National Academy of Sciences.

[11]  Cecilia Mascolo,et al.  An Empirical Study of Geographic User Activity Patterns in Foursquare , 2011, ICWSM.

[12]  Lars Backstrom,et al.  The Anatomy of the Facebook Social Graph , 2011, ArXiv.

[13]  Andreas Krause,et al.  Cost-effective outbreak detection in networks , 2007, KDD '07.

[14]  Éva Tardos,et al.  Maximizing the Spread of Influence through a Social Network , 2015, Theory Comput..

[15]  David Liben-Nowell,et al.  The link-prediction problem for social networks , 2007 .

[16]  Cyrus Shahabi,et al.  Towards integrating real-world spatiotemporal data with social networks , 2011, GIS.

[17]  Yan Liu,et al.  EBM: an entropy-based model to infer social strength from spatiotemporal data , 2013, SIGMOD '13.