IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v50y2023i5p1244-1261.html
   My bibliography  Save this article

Transit communication via Twitter during the COVID-19 pandemic

Author

Listed:
  • Wenwen Zhang
  • Camille Barchers
  • Janille Smith-Colin

Abstract

Transit providers have used social media (e.g., Twitter) as a powerful platform to shape public perception and provide essential information, especially during times of disruption and disaster. This work examines how transit agencies used Twitter during the COVID-19 pandemic to communicate with riders and how the content and general activity influence rider interaction and Twitter handle popularity. We analyzed 654,345 tweets generated by the top 40 transit agencies in the US, based on Vehicles Operated in Annual Maximum Service (VOM), from January 2020 to August 2021. We developed an analysis framework, using advanced machine learning and natural language processing models, to understand how agencies’ tweeting patterns are associated with rider interaction outcomes during the pandemic. From the transit agency perspective, we find smaller agencies tend to generate a higher percentage of COVID-related tweets and some agencies are more repetitive than their peers. Six topics (i.e., face covering, essential service appreciation, free resources, social distancing, cleaning, and service updates) were identified in the COVID-related tweets. From the followers’ interaction perspective, most agencies gained followers after the start of the pandemic (i.e., March 2020). The percentage of follower gains is positively correlated with the percentage of COVID-related tweets, tweets replying to followers, and tweets using outlinks. The average like counts per COVID-related tweet is positively correlated with the percentage of COVID-related tweets and negatively correlated with the percentage of tweets discussing social distancing and agency repetitiveness. This work can inform transportation planners and transit agencies on how to use Twitter to effectively communicate with riders to improve public perception of health and safety as it relates to transit ridership during delays and long-term disruptions such as those created by the COVID-19 public health crisis.

Suggested Citation

  • Wenwen Zhang & Camille Barchers & Janille Smith-Colin, 2023. "Transit communication via Twitter during the COVID-19 pandemic," Environment and Planning B, , vol. 50(5), pages 1244-1261, June.
  • Handle: RePEc:sae:envirb:v:50:y:2023:i:5:p:1244-1261
    DOI: 10.1177/23998083221135609
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/23998083221135609
    Download Restriction: no

    File URL: https://libkey.io/10.1177/23998083221135609?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. Brendan Pender & Graham Currie & Alexa Delbosc & Nirajan Shiwakoti, 2014. "Social Media Use during Unplanned Transit Network Disruptions: A Review of Literature," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 501-521, July.
    2. Yung-Hsiang Cheng, 2010. "Exploring passenger anxiety associated with train travel," Transportation, Springer, vol. 37(6), pages 875-896, November.
    3. Luyu Liu & Harvey J Miller & Jonathan Scheff, 2020. "The impacts of COVID-19 pandemic on public transit demand in the United States," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-22, November.
    4. Yates, Dave & Paquette, Scott, 2011. "Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake," International Journal of Information Management, Elsevier, vol. 31(1), pages 6-13.
    5. N. Nima Haghighi & Xiaoyue Cathy Liu & Ran Wei & Wenwen Li & Hu Shao, 2018. "Using Twitter data for transit performance assessment: a framework for evaluating transit riders’ opinions about quality of service," Public Transport, Springer, vol. 10(2), pages 363-377, August.
    6. Lisa Schweitzer, 2014. "Planning and Social Media: A Case Study of Public Transit and Stigma on Twitter," Journal of the American Planning Association, Taylor & Francis Journals, vol. 80(3), pages 218-238, July.
    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. Sarker, Rumana Islam & Kaplan, Sigal & Mailer, Markus & Timmermans, Harry J.P., 2019. "Applying affective event theory to explain transit users’ reactions to service disruptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 593-605.
    2. Luo, Shuli & He, Sylvia Y. & Grant-Muller, Susan & Song, Linqi, 2023. "Influential factors in customer satisfaction of transit services: Using crowdsourced data to capture the heterogeneity across individuals, space and time," Transport Policy, Elsevier, vol. 131(C), pages 173-183.
    3. Shuli Luo & Sylvia Y He, 2021. "Using data mining to explore the spatial and temporal dynamics of perceptions of metro services in China: The case of Shenzhen," Environment and Planning B, , vol. 48(3), pages 449-466, March.
    4. Pascal Un & Sonia Adelé & Flore Vallet & Jean-Marie Burkhardt, 2022. "How Does My Train Line Run? Elicitation of Six Information-Seeking Profiles of Regular Suburban Train Users," Sustainability, MDPI, vol. 14(5), pages 1-22, February.
    5. Liu, Luyu & Porr, Adam & Miller, Harvey J., 2024. "Measuring the impacts of disruptions on public transit accessibility and reliability," Journal of Transport Geography, Elsevier, vol. 114(C).
    6. Andre Carrel & Raja Sengupta & Joan L. Walker, 2017. "The San Francisco Travel Quality Study: tracking trials and tribulations of a transit taker," Transportation, Springer, vol. 44(4), pages 643-679, July.
    7. Eldeeb, Gamal & Sears, Sean & Mohamed, Moataz, 2023. "What do users want from transit? Qualitative analysis of current and potential users' perceptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    8. Mahdi Rezapour & F. Richard Ferraro, 2021. "The impact of commuters’ psychological feelings due to delay on perceived quality of a rail transport," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-8, December.
    9. Wang, Bin & Zacharias, John, 2020. "Noise, odor and passenger density in perceived crowding in public transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 215-223.
    10. Muhammad Ashraf Fauzi, 2023. "Social media in disaster management: review of the literature and future trends through bibliometric analysis," 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. 118(2), pages 953-975, September.
    11. Seyed Mohammad Hossein Moosavi & Amiruddin Ismail & Choon Wah Yuen, 2020. "Using simulation model as a tool for analyzing bus service reliability and implementing improvement strategies," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-26, May.
    12. Ni, Zi-jian & Rong, Lili & Wang, Ning & Cao, Shuo, 2019. "Knowledge model for emergency response based on contingency planning system of China," International Journal of Information Management, Elsevier, vol. 46(C), pages 10-22.
    13. Liu, Luyu & Kar, Armita & Tokey, Ahmad Ilderim & Le, Huyen T.K. & Miller, Harvey J., 2023. "Disparities in public transit accessibility and usage by people with mobility disabilities: An evaluation using high-resolution transit data," Journal of Transport Geography, Elsevier, vol. 109(C).
    14. Zhao, Dingtao & Wang, Feng & Wei, Jiuchang & Liang, Liang, 2013. "Public reaction to information release for crisis discourse by organization: Integration of online comments," International Journal of Information Management, Elsevier, vol. 33(3), pages 485-495.
    15. S M Nadim Sultan & Keshav Lall Maharjan, 2022. "Cyclone-Induced Disaster Loss Reduction by Social Media: A Case Study on Cyclone Amphan in Koyra Upazila, Khulna District, Bangladesh," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    16. Hanumantha Rao Sama & Long-Sheng Chen & Venkateswarlu Nalluri & Madhavaiah Chendragiri, 2023. "Enhancing service quality of rural public transport during the COVID-19 pandemic: a novel fuzzy approach," Public Transport, Springer, vol. 15(2), pages 479-501, June.
    17. Singh, Suraj Shirodkar & Javanmard, Reyhane & Lee, Jinhyung & Kim, Junghwan & Diab, Ehab, 2021. "The new BRT system has led to an overall increase in transit-based accessibility to essential services during the COVID-19 pandemic: Empirical evidence from Winnipeg, Canada," OSF Preprints anjd7, Center for Open Science.
    18. Lorelei Schmitt & Alexa Delbosc & Graham Currie, 2019. "Learning to use transit services: adapting to unfamiliar transit travel," Transportation, Springer, vol. 46(3), pages 1033-1049, June.
    19. Zhu, Chunxiao & Shou, Minghuan & Zhou, Yitong & Li, Wenrui, 2023. "Modeling the effect of social media on older adults’ usage intention of public transport," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 239-250.
    20. Luo, Shuli & He, Sylvia Y., 2021. "Understanding gender difference in perceptions toward transit services across space and time: A social media mining approach," Transport Policy, Elsevier, vol. 111(C), pages 63-73.

    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:sae:envirb:v:50:y:2023:i:5:p:1244-1261. 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: SAGE Publications (email available below). General contact details of provider: .

    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.