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Tweets on the Road

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  • Maxime Lenormand
  • Antònia Tugores
  • Pere Colet
  • José J Ramasco

Abstract

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.

Suggested Citation

  • Maxime Lenormand & Antònia Tugores & Pere Colet & José J Ramasco, 2014. "Tweets on the Road," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-12, August.
    • Handle: RePEc:plo:pone00:0105407
    DOI: 10.1371/journal.pone.0105407
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    References listed on IDEAS

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    Cited by:

    1. Nikolaos Askitas, 2016. "Predicting Road Conditions with Internet Search," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-12, August.
    2. Fabio Lamanna & Maxime Lenormand & María Henar Salas-Olmedo & Gustavo Romanillos & Bruno Gonçalves & José J Ramasco, 2018. "Immigrant community integration in world cities," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-19, March.
    3. Adriana Giret & Carlos Carrascosa & Vicente Julian & Miguel Rebollo & Vicente Botti, 2018. "A Crowdsourcing Approach for Sustainable Last Mile Delivery," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    4. Rene Westerholt & Enrico Steiger & Bernd Resch & Alexander Zipf, 2016. "Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-31, September.
    5. Mattia Mazzoli & Boris Diechtiareff & Antònia Tugores & Willian Wives & Natalia Adler & Pere Colet & José J Ramasco, 2020. "Migrant mobility flows characterized with digital data," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.

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