Jianghao Wang, Yichun Fan, Juan Palacios, Yuchen Chai, Nicolas Guette-Jeanrenaud, Nick Obradovich, Chenghu Zhou, Siqi Zheng: Global evidence of expressed sentiment alterations during the COVID-19 pandemic, in: Nature Human Behaviour Vol. 6, Issue 3 (March 1, 2022) pp. 349-358.
Abstract:
“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, the authors developed a global dataset of expressed sentiment indices to track national- and subnational-level affective states on a daily basis. The authors present two motivating applications using data from the first wave of Covid-19 (from January 1 to May 31, 2020). First, using regression discontinuity design, the authors provide consistent evidence that Covid-19 outbreaks caused steep declines in expressed sentiment globally, followed by asymmetric, slower recoveries. Second, applying synthetic control methods, the authors 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.”
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