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Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study.
J Med Internet Res. 2020 04 21; 22(4):e19016.JM

Abstract

BACKGROUND

The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world's health care infrastructure as well as the social, economic, and psychological well-being 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 health care 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 (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined 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, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation 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 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (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.

Authors+Show Affiliations

College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.College of Life Sciences, Kuwait University, Kuwait, Kuwait. Health Informatics Unit, Dasman Diabetes Institute, Kuwait, Kuwait.College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

32287039

Citation

Abd-Alrazaq, Alaa, et al. "Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study." Journal of Medical Internet Research, vol. 22, no. 4, 2020, pp. e19016.
Abd-Alrazaq A, Alhuwail D, Househ M, et al. Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study. J Med Internet Res. 2020;22(4):e19016.
Abd-Alrazaq, A., Alhuwail, D., Househ, M., Hamdi, M., & Shah, Z. (2020). Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study. Journal of Medical Internet Research, 22(4), e19016. https://doi.org/10.2196/19016
Abd-Alrazaq A, et al. Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study. J Med Internet Res. 2020 04 21;22(4):e19016. PubMed PMID: 32287039.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study. AU - Abd-Alrazaq,Alaa, AU - Alhuwail,Dari, AU - Househ,Mowafa, AU - Hamdi,Mounir, AU - Shah,Zubair, Y1 - 2020/04/21/ PY - 2020/03/31/received PY - 2020/04/09/accepted PY - 2020/04/09/revised PY - 2020/4/15/pubmed PY - 2020/4/28/medline PY - 2020/4/15/entrez KW - 2019-nCov KW - SARS-CoV-2 KW - Twitter KW - coronavirus, COVID-19 KW - disease surveillance KW - health informatics KW - infodemiology KW - infoveillance KW - public health KW - social media SP - e19016 EP - e19016 JF - Journal of medical Internet research JO - J Med Internet Res VL - 22 IS - 4 N2 - BACKGROUND: The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world's health care infrastructure as well as the social, economic, and psychological well-being 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 health care 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 (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined 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, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation 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 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (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. SN - 1438-8871 UR - https://news.unboundmedicine.com/medline/citation/32287039/Top_Concerns_of_Tweeters_During_the_COVID_19_Pandemic:_Infoveillance_Study_ DB - PRIME DP - Unbound Medicine ER -