Articles | Volume 4
https://doi.org/10.5194/agile-giss-4-22-2023
https://doi.org/10.5194/agile-giss-4-22-2023
06 Jun 2023
 | 06 Jun 2023

The impact of the COVID-19 pandemic on the dynamics of topics in urban green space

Nan Cui, Nick Malleson, Vikki Houlden, and Alexis Comber

Keywords: Urban green space, Topic detection, Spatial-temporal analysis, COVID-19

Abstract. Urban residents’ daily lives have been impacted by the COVID-19 pandemic in various aspects such as social, leisure, and physical activities. Fortunately, urban green spaces (UGSs) have become a main outdoor destination, due to the policies encouraging people to visit UGS and keeping them open. This study aimed to comprehensively investigate the impact of the COVID-19 pandemic on topics discussed on social media by UGS visitors over space and time. Data was collected from geo-referenced Tweets across London in spring 2019, 2020, and 2021. Structural Topic Modelling (STM) was used to identify UGS topics and describe the dynamics of topic proportions. The inverse distance weighted (IDW) interpolation method was used to explore spatial distributions of all topics. The study identified seven main types of UGS topics over all study periods, with topics such as Lockdown and exercise and Social and friends showing a decreasing trend in topic proportions, indicating that visitors' outdoor activities were restricted. The study not only identifies the main types of topics in UGS during the COVID-19 pandemic period but also reflects people’s attitudes and perceptions towards restriction measures, which can provide guidance for future urban policies, especially during crises.

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