This paper aims to understand the impact of the COVID-19 on human mobility. We explore individual traces through spatial-temporal check-ins on social media. In particular, we leverage geo-tagged tweets, to extrapolate people's geo-locations in New York City (NYC) when they check in Twitter. Building on these data, we perform gyration and travel similarity analysis to study the change of travel pattern during the pandemic. We make a comparison of users' gyration and the number of COVID-19 deaths across time. We find that (1) Users' gyration decreased by 35% after the stay-at-home order. (2) Check-in activities on social media is related to the fear of coronavirus: User's gyration has a negative correlation (-0.7) with the number of deaths across time. (3) Travel similarity decreased by 15% from March 2020 to June 2020 because many people did not travel outside after the stay-at-home order. (4) Inter-personal travel similarity among users was lower than 0.2 and individual traces of a majority of people had no overlap during the pandemic.


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    Titel :

    How the COVID-19 Pandemic Influences Human Mobility? Similarity Analysis Leveraging Social Media Data


    Beteiligte:
    Chen, Xu (Autor:in) / Di, Xuan (Autor:in)


    Erscheinungsdatum :

    2022-10-08


    Format / Umfang :

    1526624 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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