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Spatial and Temporal Evaluation of Network-Based Analysis of Human Mobility

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State of the Art Applications of Social Network Analysis

Part of the book series: Lecture Notes in Social Networks ((LNSN))

Abstract

The availability of massive network and mobility data from diverse domains has fostered the analysis of human behavior and interactions. This data availability leads to challenges in the knowledge discovery community. Several different analyses have been performed on the traces of human trajectories, such as understanding the real borders of human mobility or mining social interactions derived from mobility and viceversa. However, the data quality of the digital traces of human mobility has a dramatic impact over the knowledge that it is possible to mine, and this issue has not been thoroughly tackled in literature so far. In this chapter, we mine and analyze with complex network techniques a large dataset of human trajectories, a GPS dataset from more than 150 k vehicles in Italy. We build a multiresolution spatial grid and we map the trajectories to several complex networks, by connecting the different areas of our region of interest. We also analyze different temporal slices of the network, obtaining a dynamic perspective over its evolution. We analyze the structural properties of the temporal and geographical slices and their human mobility predictive power. The result is a significant advancement in our understanding of the data transformation process that is needed to connect mobility with social network analysis and mining.

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Notes

  1. 1.

    http://www.wheresgeorge.com/

  2. 2.

    The complete table can be retrieved at the following URL: http://www.di.unipi.it/~coscia/borders/gridstatistics.htm

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Acknowledgments

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n270833. We also acknowledge Octo Telematics S.p.A. for providing the dataset.

Author information

Authors and Affiliations

  1. CID—Harvard Kennedy School, 79 JFK Street, Cambridge, MA, USA

    Michele Coscia

  2. KDDLab ISTI-CNR, Via G. Moruzzi, 1, Pisa, Italy

    Salvatore Rinzivillo & Fosca Giannotti

  3. KDDLab University of Pisa, Largo B. Pontecorvo, 3, Pisa, Italy

    Dino Pedreschi

Authors
  1. Michele Coscia
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  2. Salvatore Rinzivillo
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  3. Fosca Giannotti
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  4. Dino Pedreschi
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Corresponding author

Correspondence to Michele Coscia .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Bilkent University, Bilkent, Turkey

    Fazli Can

  2. Department of Computer Engineering, TOBB University, Sogutozu Ankara, Turkey

    Tansel Özyer

  3. Department of Computer Engineering University Campus, Middle East Technical University, Ankara, Turkey

    Faruk Polat

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Coscia, M., Rinzivillo, S., Giannotti, F., Pedreschi, D. (2014). Spatial and Temporal Evaluation of Network-Based Analysis of Human Mobility. In: Can, F., Özyer, T., Polat, F. (eds) State of the Art Applications of Social Network Analysis. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-05912-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-05912-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05911-2

  • Online ISBN: 978-3-319-05912-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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