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

[EN] 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.The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no 318367 (EUNOIA project) and no 611307 (INSIGHT project). The work of ML has been funded under the PD/004/2013 project, from the Conselleria de Educacion, Cultura y Universidades of the Government of the Balearic Islands and from the European Social Fund through the Balearic Islands ESF operational program for 2013-2017.Picornell Tronch, M.; Ruiz Sánchez, T.; Lenormand, M.; Ramasco, JJ.; Dubernet, T.; Frías-Martínez, E. (2015). Exploring the potential of phone call data to characterize the relationship between social network and travel behavior. Transportation. 42(4):647-668. https://doi.org/10.1007/s11116-015-9594-1S647668424Ahas, R., Aasa, A., Silm, S., Tiru, M.: Daily rhythms of suburban commuters’ movements in the tallinn metropolitan area: case study with mobile positioning data. Transp. Res. 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A colorectal cancer susceptibility new variant at 4q26 in the Spanish population identified by genome-wide association analysis

This work was partially supported by the CENIT program from the Centro Tecnológico Industrial (CEN-20091016), grants from the Spanish Institute of Health Carlos III (ADE10/00026, PI09/02444, PI12/00511, Acción Transversal de Cáncer) grants from the Fondo de Investigacion Sanitaria/FEDER (08/1276, 08/0024, PS09/02368, 11/00219, 11/00681), and by COST office through COST action BM1206. SCB is supported by contracts from the Fondo de Investigación Sanitaria (CP 03-0070). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Centro Tecnológico IndustrialInstituto de Salud Carlos IIIFondo de Investigación Sanitaria / FEDE

Integrated treatment of first episode psychosis with online training (e-learning): study protocol for a randomised controlled trial

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A compendium and functional characterization of mammalian genes involved in adaptation to Arctic or Antarctic environments

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Children’s perspectives on scale response options of subjective well-being measures: A comparison between numerical and verbal-response formats

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Drosophila Araucan and Caupolican Integrate Intrinsic and Signalling Inputs for the Acquisition by Muscle Progenitors of the Lateral Transverse Fate

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Chagas Cardiomyopathy Manifestations and Trypanosoma cruzi Genotypes Circulating in Chronic Chagasic Patients

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