Investigating the civic emotion dynamics during the COVID-19 lockdown: Evidence from social media

Abstract

While quality environments (e.g., greenery) have been widely reported to alleviate residents' psychological stress during COVID-19 quarantines, this study argues that roles of the built environment and other commonly found emotion determinants can vary or reverse under strict lockdowns when human mobility is seriously restricted. We took Shanghai’s "citywide static management" as a case study and scraped over 100,000 Weibo posts between February and July 2022 to capture civic emotions before/during/after the lockdown. Natural Language Processing (NLP) was applied to grade the unique “helplessness” sentiment along with other negative emotions. Spatial regressions were utilized to investigate their determinants. We present three controversial findings: 1) Quality environments (e.g., perceived greenness, sky view) alleviated negative emotions before/after the lockdown but exacerbated stress during the lockdown, indicating that residents become more vulnerable when they lose superior access to urban amenities for which they have paid price premiums; 2) Sociodemographics’ impact on negative emotions varied significantly throughout three lockdown phases, with the elderly experiencing increased stress when losing access to emergency services; 3) Housing prices and rents inversely correlated with negative emotions (higher housing price indicated richer social resources), implying the complex interplay between residents’ socioeconomic status and well-being. Our data-driven approach effectively retraces local voices and discloses civic emotions, informing more human-centric urban management strategies to facilitate social sustainability in the face of future crises.