IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v42y2015i4p647-668.html
   My bibliography  Save this article

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

Author

Listed:
  • Miguel Picornell
  • Tomás Ruiz
  • Maxime Lenormand
  • José Ramasco
  • Thibaut Dubernet
  • Enrique Frías-Martínez

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. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Miguel Picornell & Tomás Ruiz & Maxime Lenormand & José Ramasco & Thibaut Dubernet & Enrique Frías-Martínez, 2015. "Exploring the potential of phone call data to characterize the relationship between social network and travel behavior," Transportation, Springer, vol. 42(4), pages 647-668, July.
    • Handle: RePEc:kap:transp:v:42:y:2015:i:4:p:647-668
    DOI: 10.1007/s11116-015-9594-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11116-015-9594-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11116-015-9594-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jeremy Hackney & Fabrice Marchal, 2011. "A coupled multi-agent microsimulation of social interactions and transportation behavior," Post-Print halshs-00733505, HAL.
    2. Juan Antonio Carrasco & Bernie Hogan & Barry Wellman & Eric J. Miller, 2008. "Agency In Social Activity Interactions: The Role Of Social Networks In Time And Space," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 99(5), pages 562-583, December.
    3. Santi Phithakkitnukoon & Zbigniew Smoreda & Patrick Olivier, 2012. "Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-9, June.
    4. Yim, Youngbin, 2003. "The State of Cellular Probes," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8g90p0vw, Institute of Transportation Studies, UC Berkeley.
    5. Sharmeen, Fariya & Arentze, Theo & Timmermans, Harry, 2014. "Dynamics of face-to-face social interaction frequency: role of accessibility, urbanization, changes in geographical distance and path dependence," Journal of Transport Geography, Elsevier, vol. 34(C), pages 211-220.
    6. José Moore & Juan-Antonio Carrasco & Alejandro Tudela, 2013. "Exploring the links between personal networks, time use, and the spatial distribution of social contacts," Transportation, Springer, vol. 40(4), pages 773-788, July.
    7. Juan Carrasco & Eric Miller, 2006. "Exploring the propensity to perform social activities: a social network approach," Transportation, Springer, vol. 33(5), pages 463-480, September.
    8. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
    9. Hackney, Jeremy & Marchal, Fabrice, 2011. "A coupled multi-agent microsimulation of social interactions and transportation behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 296-309, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. García-Albertos, Pedro & Picornell, Miguel & Salas-Olmedo, María Henar & Gutiérrez, Javier, 2019. "Exploring the potential of mobile phone records and online route planners for dynamic accessibility analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 294-307.
    2. Václav Plevka & Pieter Segaert & Chris M. J. Tampère & Mia Hubert, 2016. "Analysis of travel activity determinants using robust statistics," Transportation, Springer, vol. 43(6), pages 979-996, November.
    3. Sheng Wei & Jinfu Yuan & Yanning Qiu & Xiali Luan & Shanrui Han & Wen Zhou & Chi Xu, 2017. "Exploring the potential of open big data from ticketing websites to characterize travel patterns within the Chinese high-speed rail system," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-13, June.
    4. Eszter Bokányi & Zsófia Kallus & István Gódor, 2021. "Collective sensing of evolving urban structures: From activity-based to content-aware social monitoring," Environment and Planning B, , vol. 48(1), pages 115-131, January.
    5. Deng, Yiling & Zhao, Pengjun, 2022. "The impact of new metro on travel behavior: Panel analysis using mobile phone data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 46-57.
    6. Xiaofan Liang & Seolha Lee & Hanzhou Chen & Benjamin de la Peña & Clio Andris, 2022. "Characteristics of Jetters and Little Boxes: An Extensibility Study Using the Neighborhood Connectivity Survey," Social Inclusion, Cogitatio Press, vol. 10(3), pages 221-232.
    7. Sheng Wei & Lei Wang, 2020. "Examining the population flow network in China and its implications for epidemic control based on Baidu migration data," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-10, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Parady, Giancarlos & Frei, Andreas & Kowald, Matthias & Guidon, Sergio & Wicki, Michael & van den Berg, Pauline & Carrasco, Juan-Antonio & Arentze, Theo & Timmermans, Harry & Wellman, Barry & Takami, , 2021. "A comparative study of social interaction frequencies among social network members in five countries," Journal of Transport Geography, Elsevier, vol. 90(C).
    2. Fariya Sharmeen & Theo Arentze & Harry Timmermans, 2015. "Predicting the evolution of social networks with life cycle events," Transportation, Springer, vol. 42(5), pages 733-751, September.
    3. Lin, Tao & Wang, Donggen & Zhou, Meng, 2018. "Residential relocation and changes in travel behavior: what is the role of social context change?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 360-374.
    4. Kii, Masanobu & Nakanishi, Hitomi & Nakamura, Kazuki & Doi, Kenji, 2016. "Transportation and spatial development: An overview and a future direction," Transport Policy, Elsevier, vol. 49(C), pages 148-158.
    5. Masashi Okushima, 2015. "Simulating social influences on sustainable mobility shifts for heterogeneous agents," Transportation, Springer, vol. 42(5), pages 827-855, September.
    6. Wang, Yaoli & Kutadinata, Ronny & Winter, Stephan, 2019. "The evolutionary interaction between taxi-sharing behaviours and social networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 170-180.
    7. Di Ciommo, Floridea & Comendador, Julio & López-Lambas, María Eugenia & Cherchi, Elisabetta & Ortúzar, Juan de Dios, 2014. "Exploring the role of social capital influence variables on travel behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 46-55.
    8. Maxime Lenormand & Miguel Picornell & Oliva G Cantú-Ros & Antònia Tugores & Thomas Louail & Ricardo Herranz & Marc Barthelemy & Enrique Frías-Martínez & José J Ramasco, 2014. "Cross-Checking Different Sources of Mobility Information," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    9. Lin, Tao & Wang, Donggen, 2015. "Tradeoffs between in- and out-of-residential neighborhood locations for discretionary activities and time use: do social contexts matter?," Journal of Transport Geography, Elsevier, vol. 47(C), pages 119-127.
    10. Hackney, Jeremy & Marchal, Fabrice, 2011. "A coupled multi-agent microsimulation of social interactions and transportation behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 296-309, May.
    11. Kim, Jinhee & Rasouli, Soora & Timmermans, Harry, 2014. "Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 71-85.
    12. Li Shi & Lun Wu & Guanghua Chi & Yu Liu, 2016. "Geographical impacts on social networks from perspectives of space and place: an empirical study using mobile phone data," Journal of Geographical Systems, Springer, vol. 18(4), pages 359-376, October.
    13. Coutts, Steven & Aird, Bria & Mitra, Raktim & Siemiatycki, Matti, 2018. "Does commute influence post-secondary Students' social capital? A study of campus participation at four universities in Toronto, Canada," Journal of Transport Geography, Elsevier, vol. 70(C), pages 172-181.
    14. Przemyslaw A Grabowicz & José J Ramasco & Bruno Gonçalves & Víctor M Eguíluz, 2014. "Entangling Mobility and Interactions in Social Media," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-12, March.
    15. Xiangyu Chang & Jingzhou Shen & Xiaoling Lu & Shuai Huang, 2018. "Statistical patterns of human mobility in emerging Bicycle Sharing Systems," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-16, March.
    16. Stanley, Janet & Stanley, John & Vella-Brodrick, Dianne & Currie, Graham, 2010. "The place of transport in facilitating social inclusion via the mediating influence of social capital," Research in Transportation Economics, Elsevier, vol. 29(1), pages 280-286.
    17. Ettema, Dick & Schwanen, Tim, 2012. "A relational approach to analysing leisure travel," Journal of Transport Geography, Elsevier, vol. 24(C), pages 173-181.
    18. Wei, Fangfang & Jia, Ning & Ma, Shoufeng, 2016. "Day-to-day traffic dynamics considering social interaction: From individual route choice behavior to a network flow model," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 335-354.
    19. Matous, Petr & Todo, Yasuyuki & Mojo, Dagne, 2013. "Boots are made for walking: interactions across physical and social space in infrastructure-poor regions," Journal of Transport Geography, Elsevier, vol. 31(C), pages 226-235.
    20. Hagiladi, Na'amah & O. Plaut, Pnina, 2021. "Social networks' group tie strength and travel behavior," Journal of Transport Geography, Elsevier, vol. 93(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:transp:v:42:y:2015:i:4:p:647-668. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.