4.7 Article

Exploring public values through Twitter data associated with urban parks pre- and post- COVID-19

期刊

LANDSCAPE AND URBAN PLANNING
卷 227, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.landurbplan.2022.104517

关键词

Urban greenspaces; Social media; Big data; Topic modeling; Pandemic; Public values; GSDMM topic modeling

资金

  1. USDA Forest Service [16-JV-11330144-065]

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Urban parks have become popular destinations for daily fitness activities and for people to escape their homes during the COVID-19 pandemic. This study examines how public values associated with NYC parks have changed before and after COVID-19 using social media data from Twitter. The results show that while some parks continue to be valued for physical activity and contact with nature, concerns about maintaining physical distance in crowded parks have also emerged.
Since school and business closures due to the evolving COVID-19 outbreak, urban parks have been a popular destination, offering spaces for daily fitness activities and an escape from the home environment. There is a need for evidence for parks and recreation departments and agencies to base decisions when adapting policies in response to the rapid change in demand and preferences during the pandemic. The application of social media data analytic techniques permits a qualitative and quantitative big-data approach to gain unobtrusive and prompt insights on how parks are valued. This study investigates how public values associated with NYC parks has shifted between pre- COVID (i.e., from March 2019 to February 2020) and post- COVID (i.e., from March 2020 to February 2021) through a social media microblogging platform -Twitter. A topic modeling technique for short text identified common traits of the changes in Twitter topics regarding impressions and values associated with the parks over two years. While the NYC lockdown resulted in much fewer social activities in parks, some parks continued to be valued for physical activity and nature contact during the pandemic. Concerns about people not keeping physical distance arose in parks where frequent human interactions and crowding seemed to cause a higher probability of the coronavirus transmission. This study demonstrates social media data could be used to capture park values and be specific per park. Results could inform park management during disruptions when use is altered and the needs of the public may be changing.

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