@Article{info:doi/10.2196/25108,
author="Lyu, Joanne Chen
and Luli, Garving K",
title="Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study",
journal="J Med Internet Res",
year="2021",
month="Feb",
day="9",
volume="23",
number="2",
pages="e25108",
keywords="COVID-19; CDC; Twitter; public discussion; public opinion; social media; data mining",
abstract="Background: The Centers for Disease Control and Prevention (CDC) is a national public health protection agency in the United States. With the escalating impact of the COVID-19 pandemic on society in the United States and around the world, the CDC has become one of the focal points of public discussion. Objective: This study aims to identify the topics and their overarching themes emerging from the public COVID-19-related discussion about the CDC on Twitter and to further provide insight into public's concerns, focus of attention, perception of the CDC's current performance, and expectations from the CDC. Methods: Tweets were downloaded from a large-scale COVID-19 Twitter chatter data set from March 11, 2020, when the World Health Organization declared COVID-19 a pandemic, to August 14, 2020. We used R (The R Foundation) to clean the tweets and retain tweets that contained any of five specific keywords---cdc, CDC, centers for disease control and prevention, CDCgov, and cdcgov---while eliminating all 91 tweets posted by the CDC itself. The final data set included in the analysis consisted of 290,764 unique tweets from 152,314 different users. We used R to perform the latent Dirichlet allocation algorithm for topic modeling. Results: The Twitter data generated 16 topics that the public linked to the CDC when they talked about COVID-19. Among the topics, the most discussed was COVID-19 death counts, accounting for 12.16{\%} (n=35,347) of the total 290,764 tweets in the analysis, followed by general opinions about the credibility of the CDC and other authorities and the CDC's COVID-19 guidelines, with over 20,000 tweets for each. The 16 topics fell into four overarching themes: knowing the virus and the situation, policy and government actions, response guidelines, and general opinion about credibility. Conclusions: Social media platforms, such as Twitter, provide valuable databases for public opinion. In a protracted pandemic, such as COVID-19, quickly and efficiently identifying the topics within the public discussion on Twitter would help public health agencies improve the next-round communication with the public. ",
issn="1438-8871",
doi="10.2196/25108",
url="http://www.jmir.org/2021/2/e25108/",
url="https://doi.org/10.2196/25108",
url="http://www.ncbi.nlm.nih.gov/pubmed/33497351"
}