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Twitter Subjective Well-Being Indicator During COVID-19 Pandemic A Cross-Country Comparative Study

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Document pages: 31 pages

Abstract: This study analyzes the impact of the COVID-19 pandemic on the subjectivewell-being as measured through Twitter data indicators for Japan and Italy. Itturns out that, overall, the subjective well-being dropped by 11.7 for Italyand 8.3 for Japan in the first nine months of 2020 compared to the last twomonths of 2019 and even more compared to the historical mean of the indexes.Through a data science approach we try to identify the possible causes of thisdrop down by considering several explanatory variables including, climate andair quality data, number of COVID-19 cases and deaths, Facebook Covid and flusymptoms global survey, Google Trends data and coronavirus-related searches,Google mobility data, policy intervention measures, economic variables andtheir Google Trends proxies, as well as health and stress proxy variables basedon big data. We show that a simple static regression model is not able tocapture the complexity of well-being and therefore we propose a dynamic elasticnet approach to show how different group of factors may impact the well-beingin different periods, even over a short time length, and showing furthercountry-specific aspects. Finally, a structural equation modeling analysistries to address the causal relationships among the COVID-19 factors andsubjective well-being showing that, overall, prolonged mobilityrestrictions,flu and Covid-like symptoms, economic uncertainty, socialdistancing and news about the pandemic have negative effects on the subjectivewell-being.

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