Outlet Title

AMCIS 2020 Proceedings

Document Type

Conference Proceeding

Publication Date

2020

Abstract

The recent outbreak of the coronavirus (COVID-19) brought with its public concerns and fears about a global epidemic. With the increase in the popularity, usage, and reach of social media, this research examined the early public outlook on COVID-19 using SM-Platform, Twitter.com. The current study employed a mixed-method approach in collecting and analyzing public tweets by combining quantitative sentiment analysis with a qualitative thematic analysis. Our results revealed positive sentiment prior to the spread of the disease. The sentiment then turned negative as the disease spread, accompanied by a large amount of fear as rumors. In a thematic analysis we also uncovered nine key topics on the disease including, but not limited to, prevention, symptoms and spread of disease. Our study will provide an understanding of social media and public health outbreak surveillance. The findings of the research revealed the usefulness of twitter mining to illuminate public health education.

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