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

From a public health perspective, the ability to analyze Twitter feeds in real-time and the potential to individually target segments of the population with high-impact messages based on their information needs and sentiment could be an extremely powerful tool, potentially more effective than any other communication medium. To date, bots (autonomous programs able to interact with computer systems or users) have often been used on Twitter for advertising or to promulgate malicious or false content [34, 35] . However, public health and governmental organizations like the WHO or the CDC should invest in this new technology. For example, deploying autonomous tools that identify tweets by users who are fearful of contracting COVID-19 could be used to send individually targeted messages that provide reassurance and education on preventive measures such as handwashing. Tailoring automatic responses to the sentiments and content of tweets has the potential to engage more Twitter users on public health topics and to redirect the discussion to useful, accurate information.