Tracking collective emotions in 16 countries during COVID-19: a novel methodology for identifying major emotional events using Twitter - Chauhan, Apurv; Belhekar, Vivek; Sehgal, Surbhi; Singh, Himanshu; Prakash, Jay (Frontiers in Psychology, 2024)
Using messages posted on Twitter, this paper develops a new approach to estimating daily levels of collective emotions (CE) within countries in relation to events of collective significance. It applies time-series analytic approaches to develop and demonstrate a novel application of CE to identify emotional events that are significant at the societal level. This paper analyses over 200 million words from over 10 million Twitter messages posted in sixteen countries during the first 120 days of the COVID-19 pandemic. Daily levels of collective anxiety and positive emotions were estimated using a novel application of Linguistic Inquiry and Word Counter’s (LIWC) psychologically validated lexicon. This provided two time series measurements of collective emotions which were analysed for structural breaks which mark a significant change in a series due to an external shock. External shocks to collective emotions come from events that are of shared emotional relevance and this study develops a new approach to identifying them. In the COVID-19 Twitter posts used in the study, analysis of structural breaks showed that in all 16 countries, a reduction in collective anxiety and increase in positive emotions followed WHO’s declaration of COVID-19 as a global pandemic. Announcements of economic support packages and social restrictions also had similar impacts in some countries. This indicates that reduction of uncertainty around the evolving COVID-19 situation had a positive emotional impact on people in all the countries in the study. The paper contributes to the field of CE and applied research in collective psychological phenomena.