Transportation

, Volume 42, Issue 4, pp 647–668

Exploring the potential of phone call data to characterize the relationship between social network and travel behavior

  • Miguel Picornell
  • Tomás Ruiz
  • Maxime Lenormand
  • José J. Ramasco
  • Thibaut Dubernet
  • Enrique Frías-Martínez
Article

DOI: 10.1007/s11116-015-9594-1

Cite this article as:
Picornell, M., Ruiz, T., Lenormand, M. et al. Transportation (2015) 42: 647. doi:10.1007/s11116-015-9594-1

Abstract

Social network contacts have significant influence on individual travel behavior. However, transport models rarely consider social interaction. One of the reasons is the difficulty to properly model social influence based on the limited data available. Non-conventional, passively collected data sources, such as Twitter, Facebook or mobile phones, provide large amounts of data containing both social interaction and spatiotemporal information. The analysis of such data opens an opportunity to better understand the influence of social networks on travel behavior. The main objective of this paper is to examine the relationship between travel behavior and social networks using mobile phone data. A huge dataset containing billions of registers has been used for this study. The paper analyzes the nature of co-location events and frequent locations shared by social network contacts, aiming not only to provide understanding on why users share certain locations, but also to quantify the degree in which the different types of locations are shared. Locations have been classified as frequent (home, work and other) and non-frequent. A novel approach to identify co-location events based on the intersection of users’ mobility models has been proposed. Results show that other locations different from home and work are frequently associated to social interaction. Additionally, the importance of non-frequent locations in co-location events is shown. Finally, the potential application of the data analysis results to improve activity-based transport models and assess transport policies is discussed.

Keywords

Travel behavior Social network Mobile phone Call Detail Record Activity-based modelling 

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Miguel Picornell
    • 1
  • Tomás Ruiz
    • 2
  • Maxime Lenormand
    • 3
  • José J. Ramasco
    • 3
  • Thibaut Dubernet
    • 4
  • Enrique Frías-Martínez
    • 5
  1. 1.Nommon Solutions and TechnologiesMadridSpain
  2. 2.Universitat Politècnica de ValènciaValènciaSpain
  3. 3.Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB)Palma de MallorcaSpain
  4. 4.Institute for Transport Planning and Systems (IVT)ETH ZurichZurichSwitzerland
  5. 5.Telefonica ResearchMadridSpain

Personalised recommendations