Article ID: | iaor201526165 |
Volume: | 42 |
Issue: | 4 |
Start Page Number: | 647 |
End Page Number: | 668 |
Publication Date: | Jul 2015 |
Journal: | Transportation |
Authors: | Ruiz Toms, Picornell Miguel, Lenormand Maxime, Ramasco Jos, Dubernet Thibaut, Fras-Martnez Enrique |
Keywords: | behaviour |
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 (