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The COVID-19 pandemic has claimed millions of lives worldwide and elicitedheightened emotions. This study examines the expression of various emotionspertaining to COVID-19 in the United States and India as manifested in over 54million tweets, covering the fifteen-month period from February 2020 throughApril 2021, a period which includes the beginnings of the huge and disastrousincrease in COVID-19 cases that started to ravage India in March 2021.Employing pre-trained emotion analysis and topic modeling algorithms, fourdistinct types of emotions (fear, anger, happiness, and sadness) and theirtime- and location-associated variations were examined. Results revealedsignificant country differences and temporal changes in the relativeproportions of fear, anger, and happiness, with fear declining and anger andhappiness fluctuating in 2020 until new situations over the first four monthsof 2021 reversed the trends. Detected differences are discussed briefly interms of the latent topics revealed and through the lens of appraisal theoriesof emotions, and the implications of the findings are discussed.

How People Respond to the COVID-19 Pandemic on Twitter: A Comparative Analysis of Emotional Expressions from US and India