Top concerns of tweeters during the COVID-19 pandemic: A surveillance study.

BACKGROUND: The recent COVID-19 pandemic is taking a toll on the world's healthcare infrastructure as well as the social, economic, and psychological wellbeing of humanity. Individuals, organizations and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19. Analyzing such information can help policy makers and healthcare organizations assess the needs of their stakeholders and address them appropriately.

OBJECTIVE: This study aims to identify the main topics posted by Twitter users related to the COVID-19 pandemic.

METHODS: Leveraging a set of tools (Twitter's search Application Programming Interface, Tweepy Python library, and PostgreSQL database) and using a set of pre-defined search terms (corona, 2019-nCov, and COVID-19), we extracted the text and metadata (number of likes and retweets, and user profile information including the number of followers) of public English language tweets from February 2, 2020 up to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged Latent Dirichlet Allocation (LDA) for topic modeling to identify topics discussed in the tweets. We also performed sentiment analysis and extracted the mean number of retweets, likes, and followers for each topic and calculated the interaction rate per topic.

RESULTS: Out of approximately 2.8 million tweets included, 167,073 unique tweets from 160,829 unique users met the inclusion criteria. Our analysis identified twelve topics which were grouped into four main themes: (i) Origin of the virus, (ii) its sources, (iii) its impact on people, countries, and the economy, and (iv) ways of mitigating the risk of infection. The mean sentiment was positive for ten topics and negative for two topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2,722 (increased racism) to 13,413 (economic losses). The highest mean of likes for the tweets was 15.4 (economic loss) while the lowest was 3.94 (travel bans and warnings).

CONCLUSIONS: Public health crisis response activities on the ground and online are becoming increasingly simultaneous and intertwined. Social media provides an opportunity to directly communicate health information to the public. Health systems should work on building national and international disease detection and surveillance systems through monitoring social media. There is also a need for a more proactive and agile public health presence on social media to combat the spread of fake news.