IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0131469.html
   My bibliography  Save this article

Understanding Human Mobility from Twitter

Author

Listed:
  • Raja Jurdak
  • Kun Zhao
  • Jiajun Liu
  • Maurice AbouJaoude
  • Mark Cameron
  • David Newth

Abstract

Understanding human mobility is crucial for a broad range of applications from disease prediction to communication networks. Most efforts on studying human mobility have so far used private and low resolution data, such as call data records. Here, we propose Twitter as a proxy for human mobility, as it relies on publicly available data and provides high resolution positioning when users opt to geotag their tweets with their current location. We analyse a Twitter dataset with more than six million geotagged tweets posted in Australia, and we demonstrate that Twitter can be a reliable source for studying human mobility patterns. Our analysis shows that geotagged tweets can capture rich features of human mobility, such as the diversity of movement orbits among individuals and of movements within and between cities. We also find that short- and long-distance movers both spend most of their time in large metropolitan areas, in contrast with intermediate-distance movers’ movements, reflecting the impact of different modes of travel. Our study provides solid evidence that Twitter can indeed be a useful proxy for tracking and predicting human movement.

Suggested Citation

  • Raja Jurdak & Kun Zhao & Jiajun Liu & Maurice AbouJaoude & Mark Cameron & David Newth, 2015. "Understanding Human Mobility from Twitter," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-16, July.
  • Handle: RePEc:plo:pone00:0131469
    DOI: 10.1371/journal.pone.0131469
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0131469
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0131469&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0131469?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
    ---><---

    References listed on IDEAS

    as
    1. Julie Fournet & Alain Barrat, 2014. "Contact Patterns among High School Students," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-17, September.
    2. Anastasios Noulas & Salvatore Scellato & Renaud Lambiotte & Massimiliano Pontil & Cecilia Mascolo, 2012. "A Tale of Many Cities: Universal Patterns in Human Urban Mobility," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-10, May.
    3. Ciro Cattuto & Wouter Van den Broeck & Alain Barrat & Vittoria Colizza & Jean-François Pinton & Alessandro Vespignani, 2010. "Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks," PLOS ONE, Public Library of Science, vol. 5(7), pages 1-9, July.
    4. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Huang, Feihu & Qiao, Shaojie & Peng, Jian & Guo, Bing & Xiong, Xi & Han, Nan, 2019. "A movement model for air passengers based on trip purpose," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 798-808.
    3. Douglas W Lowery-North & Vicki Stover Hertzberg & Lisa Elon & George Cotsonis & Sarah A Hilton & Christopher F Vaughns II & Eric Hill & Alok Shrestha & Alexandria Jo & Nathan Adams, 2013. "Measuring Social Contacts in the Emergency Department," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-9, August.
    4. Chaogui Kang & Yu Liu & Diansheng Guo & Kun Qin, 2015. "A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    5. Wang, Wenjun & Pan, Lin & Yuan, Ning & Zhang, Sen & Liu, Dong, 2015. "A comparative analysis of intra-city human mobility by taxi," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 134-147.
    6. Barmak, D.H. & Dorso, C.O. & Otero, M., 2016. "Modelling dengue epidemic spreading with human mobility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 129-140.
    7. Saberi, Meead & Ghamami, Mehrnaz & Gu, Yi & Shojaei, Mohammad Hossein (Sam) & Fishman, Elliot, 2018. "Understanding the impacts of a public transit disruption on bicycle sharing mobility patterns: A case of Tube strike in London," Journal of Transport Geography, Elsevier, vol. 66(C), pages 154-166.
    8. Chen, Ya & Li, Xue & Zhang, Richong & Huang, Zi-Gang & Lai, Ying-Cheng, 2020. "Instantaneous success and influence promotion in cyberspace — how do they occur?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    9. Raja Jurdak, 2013. "The Impact of Cost and Network Topology on Urban Mobility: A Study of Public Bicycle Usage in 2 U.S. Cities," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-6, November.
    10. Meead Saberi & Taha H. Rashidi & Milad Ghasri & Kenneth Ewe, 2018. "A Complex Network Methodology for Travel Demand Model Evaluation and Validation," Networks and Spatial Economics, Springer, vol. 18(4), pages 1051-1073, December.
    11. Rezapour, Shabnam & Baghaian, Atefe & Naderi, Nazanin & Sarmiento, Juan P., 2023. "Infection transmission and prevention in metropolises with heterogeneous and dynamic populations," European Journal of Operational Research, Elsevier, vol. 304(1), pages 113-138.
    12. Stanislav Sobolevsky & Izabela Sitko & Remi Tachet des Combes & Bartosz Hawelka & Juan Murillo Arias & Carlo Ratti, 2016. "Cities through the Prism of People’s Spending Behavior," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-19, February.
    13. Siqin Wang & Mengxi Zhang & Tao Hu & Xiaokang Fu & Zhe Gao & Briana Halloran & Yan Liu, 2021. "A Bibliometric Analysis and Network Visualisation of Human Mobility Studies from 1990 to 2020: Emerging Trends and Future Research Directions," Sustainability, MDPI, vol. 13(10), pages 1-22, May.
    14. Xiang-Wen Wang & Xiao-Pu Han & Bing-Hong Wang, 2014. "Correlations and Scaling Laws in Human Mobility," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    15. Nimrod Serok & Efrat Blumenfeld-Lieberthal, 2015. "A Simulation Model for Intra-Urban Movements," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    16. Wim Ectors & Bruno Kochan & Davy Janssens & Tom Bellemans & Geert Wets, 2019. "Exploratory analysis of Zipf’s universal power law in activity schedules," Transportation, Springer, vol. 46(5), pages 1689-1712, October.
    17. Fan Yang & Zhenxing Yao & Fan Ding & Huachun Tan & Bin Ran, 2019. "Understanding Urban Mobility Pattern with Cellular Phone Data: A Case Study of Residents and Travelers in Nanjing," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
    18. Sanja Šćepanović & Igor Mishkovski & Pan Hui & Jukka K Nurminen & Antti Ylä-Jääski, 2015. "Mobile Phone Call Data as a Regional Socio-Economic Proxy Indicator," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.
    19. 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.
    20. Funel, Agostino, 2022. "A method to compute the communicability of nodes through causal paths in temporal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0131469. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.