IDEAS home Printed from https://ideas.repec.org/a/igg/jepr00/v10y2021i2p66-79.html
   My bibliography  Save this article

Changing Mobility Lifestyle: A Case Study on the Impact of COVID-19 Using Personal Google Locations Data

Author

Listed:
  • Vít Pászto

    (Palacký University Olomouc, Czech Republic & Moravian Business College Olomouc, Czech Republic)

  • Jaroslav Burian

    (Palacký University Olomouc, Czech Republic & Moravian Business College Olomouc, Czech Republic)

  • Karel Macků

    (Palacký University Olomouc, Czech Republic)

Abstract

The article is focused on a detailed micro-study describing changes in the behaviour of the authors in three months before and during the COVID-19 pandemic. The study is based on data from Google Location Service. Despite the fact it evaluates only three people and the study cannot be sufficiently representative, it is a unique example of possible data processing at such a level of accuracy. The most significant changes in the behaviour of authors before and during the COVID-19 quarantine are described and interpreted in detail. Another purpose of the article is to point out the possibilities of analytical processing of Google Location while being aware of personal data protection issues. The authors recognize that by visualizing the real motion data, one partially discloses their privacy, but one considers it very valuable to show how detailed data Google collects about the population and how such data can be used effectively.

Suggested Citation

  • Vít Pászto & Jaroslav Burian & Karel Macků, 2021. "Changing Mobility Lifestyle: A Case Study on the Impact of COVID-19 Using Personal Google Locations Data," International Journal of E-Planning Research (IJEPR), IGI Global, vol. 10(2), pages 66-79, April.
  • Handle: RePEc:igg:jepr00:v:10:y:2021:i:2:p:66-79
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJEPR.20210401.oa6
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Daniel Monsivais & Asim Ghosh & Kunal Bhattacharya & Robin I M Dunbar & Kimmo Kaski, 2017. "Tracking urban human activity from mobile phone calling patterns," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-16, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lucian-Ionel Cioca & Mihaela Laura Bratu, 2021. "Sustainable Education in the Context of COVID-19: Study of the Social Perception and Well-Being of Students at the Faculty of Engineering in Sibiu, Romania," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    2. Ömer Kaya & Kadir Diler Alemdar & Tiziana Campisi & Ahmet Tortum & Merve Kayaci Çodur, 2021. "The Development of Decarbonisation Strategies: A Three-Step Methodology for the Suitable Analysis of Current EVCS Locations Applied to Istanbul, Turkey," Energies, MDPI, vol. 14(10), pages 1-21, May.
    3. Artur Strzelecki & Ana Azevedo & Mariia Rizun & Paulina Rutecka & Kacper Zagała & Karina Cicha & Alexandra Albuquerque, 2022. "Human Mobility Restrictions and COVID-19 Infection Rates: Analysis of Mobility Data and Coronavirus Spread in Poland and Portugal," IJERPH, MDPI, vol. 19(21), pages 1-25, November.

    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. Robert Stewart & Marie Urban & Samantha Duchscherer & Jason Kaufman & April Morton & Gautam Thakur & Jesse Piburn & Jessica Moehl, 2016. "A Bayesian machine learning model for estimating building occupancy from open source data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(3), pages 1929-1956, April.
    2. He, Yifan & Zhao, Chen & Zeng, An, 2022. "Ranking locations in a city via the collective home-work relations in human mobility data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    3. Sarah Williams & Elizabeth Currid-Halkett, 2014. "Industry in Motion: Using Smart Phones to Explore the Spatial Network of the Garment Industry in New York City," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Michele Coscia & Ricardo Hausmann, 2015. "Evidence That Calls-Based and Mobility Networks Are Isomorphic," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-15, December.
    11. Andrew Mondschein, 2015. "Five-star transportation: using online activity reviews to examine mode choice to non-work destinations," Transportation, Springer, vol. 42(4), pages 707-722, July.
    12. Han Wang & Damien Fay & Kenneth N. Brown & Liam Kilmartin, 2016. "Modelling revenue generation in a dynamically priced mobile telephony service," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 62(4), pages 711-734, August.
    13. Silver, Grant & Akbarzadeh, Meisam & Estrada, Ernesto, 2018. "Tuned communicability metrics in networks. The case of alternative routes for urban traffic," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 402-413.
    14. 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.
    15. 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.
    16. Yang, Zimo & Lian, Defu & Yuan, Nicholas Jing & Xie, Xing & Rui, Yong & Zhou, Tao, 2017. "Indigenization of urban mobility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 232-243.
    17. Adler, Nicole & Brudner, Amir & Gallotti, Riccardo & Privitera, Filippo & Ramasco, José J., 2022. "Does big data help answer big questions? The case of airport catchment areas & competition," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 444-467.
    18. Huang, Hai-Jun & Xia, Tian & Tian, Qiong & Liu, Tian-Liang & Wang, Chenlan & Li, Daqing, 2020. "Transportation issues in developing China's urban agglomerations," Transport Policy, Elsevier, vol. 85(C), pages 1-22.
    19. Priscila Santin & Fernanda R. Gubert & Mauro Fonseca & Anelise Munaretto & Thiago Henrique Silva, 2020. "Characterization of Public Transit Mobility Patterns of Different Economic Classes," Sustainability, MDPI, vol. 12(22), pages 1-24, November.
    20. Minda Hu & Mayank Kejriwal, 2022. "Measuring spatio-textual affinities in twitter between two urban metropolises," Journal of Computational Social Science, Springer, vol. 5(1), pages 227-252, May.

    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:igg:jepr00:v:10:y:2021:i:2:p:66-79. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.