Global evidence of expressed sentiment alterations during the COVID-19 pandemic

The COVID-19 pandemic has created unprecedented burdens on people's physical health and subjective well-being. While countries worldwide have developed platforms to track the evolution of COVID-19 infections and deaths, frequent global measurements of affective states to gauge the emotional impacts of pandemic and related policy interventions remain scarce. Using 654 million geotagged social media posts in over 100 countries, covering 74% of world population, coupled with state-of-the-art natural language processing techniques, we develop a global dataset of expressed sentiment indices to track national- and subnational-level affective states on a daily basis. We present two motivating applications using data from the first wave of COVID-19 (from 1 January to 31 May 2020). First, using regression discontinuity design, we provide consistent evidence that COVID-19 outbreaks caused steep declines in expressed sentiment globally, followed by asymmetric, slower recoveries. Second, applying synthetic control methods, we find moderate to no effects of lockdown policies on expressed sentiment, with large heterogeneity across countries. This study shows how social media data, when coupled with machine learning techniques, can provide real-time measurements of affective states. Using tweets in over 100 countries, Wang et al. examine evidence of global sentiment during the COVID-19 pandemic. They find that COVID-19 outbreaks caused a decline in sentiment worldwide, and the effects of lockdowns differed across countries.

Automated summary

The COVID-19 pandemic has had unprecedented effects on people's physical health and subjective well-being. This study uses social media data and machine learning techniques to develop a global dataset of expressed sentiment indices, allowing for real-time tracking of affective states. The findings show that global sentiment declined sharply during the COVID-19 outbreak and exhibited asymmetric, slower recoveries, while the effects of lockdown policies on sentiment varied greatly across countries.