An ""Infodemic"": Leveraging High-Volume Twitter Data to Understand Public Sentiment for the COVID-19 Outbreak

Richard J. Medford; Sameh N. Saleh; Andrew Sumarsono; Trish M. Perl; Christoph U. Lehmann

Fear was the most common emotion expressed in nearly 49.5% of all tweets with topics ranging from fear of infection, death, and inability to travel as well as emotional distress and fear regarding the effect on the economy and politics. [Examples: "Coronavirus: Virus fears trigger Shanghai face mask shortage" and "Oil falls below $60 as China coronavirus fears accelerate"] Surprise was the second most common emotion present in 29.3% of tweets. [Example: "The Wuhan virus is more critical than expected! Don't forget to wear [a] face mask(surgical mask)!"]. Anger followed and included themes of inadequate governmental reactions, isolation and quarantine, lack of supplies, and lack of information. [Examples: "Wuhan coronavirus: Hong Kong police, protesters clash as anger erupts over proposal to use housing block as quarantine site" and "11 million city on a lockdown!!!"]. The least common predominant emotions found in tweets were sadness, joy, and disgust ( Figure 4a ). We analyzed tweets for positive, neutral, or negative emotional valence. Tweets with a negative emotion were more common than neutral and positive tweets and increased at a faster rate over time (Figure 4b ).