2014/05/20 by Maxime Lenormand, Antònia Tugores, Pere Colet +1 · 46 citations
Computer Science · Engineering · Medicine · Physics and Astronomy · Social Sciences · #Business #Complex Network Analysis Techniques #Computer science #Data-Driven Disease Surveillance #Engineering #Geography #Human Mobility and Location-Based Analysis #Social media #Transport engineering #World Wide Web #cs.CY #cs.SI #physics.soc-ph
paper · pdf · doi:10.1371/journal.pone.0105407
published in PLoS ONE 9(8), e105407 (Public Library of Science) · 15 pages, 17 figures
arxiv created 2014/05/20 · openalex publication_date 2014/08/20 · arxiv updated 2014/08/26 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
The pervasiveness of mobile devices, which is increasing daily, is generating a vast amount of geo-located data allowing us to gain further insights into human behaviors. In particular, this new technology enables users to communicate through mobile social media applications, such as Twitter, anytime and anywhere. Thus, geo-located tweets offer the possibility to carry out in-depth studies on human mobility. In this paper, we study the use of Twitter in transportation by identifying tweets posted from roads and rails in Europe between September 2012 and November 2013. We compute the percentage of highway and railway segments covered by tweets in 39 countries. The coverages are very different from country to country and their variability can be partially explained by differences in Twitter penetration rates. Still, some of these differences might be related to cultural factors regarding mobility habits and interacting socially online. Analyzing particular road sectors, our results show a positive correlation between the number of tweets on the road and the Average Annual Daily Traffic on highways in France and in the UK. Transport modality can be studied with these data as well, for which we discover very heterogeneous usage patterns across the continent.