Table 1.

Summary of key studies on the COVID-19 pandemic using social media data.

Source	Social media platform	Data set	Time period	Key findings
Abd-Alrazaq et al, 2020 [10]	Twitter	167,073 tweets	Tweets from February 2 to March 15, 2020	Identified 12 topics that were grouped into four themes, viz the origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating infection.
Li et al, 2020 [11]	Weibo	115,299 posts	Posts from December 23, 2019, to January 30, 2020	Positive correlation between the number of Weibo posts and number of reported cases in Wuhan. Qualitative analysis of 11,893 posts revealed main themes of disease causes, changing epidemiological characteristics, and public reaction to outbreak control and response measures.
Shen et al, 2020 [12]	Weibo	15 million posts	Posts from November 1, 2019, to March 31, 2020	Developed a classifier to identify “sick posts” pertaining to COVID-19. The number of sick posts positively predicted the officially reported COVID-19 cases up to 14 days ahead of official statistics.
Sarker et al, 2020 [13]	Twitter	499,601 tweets from 305 users who self-disclosed their COVID-19 test results	N/Aa	203 users who tested positive for COVID-19 reported their symptoms: fever/pyrexia, cough, body ache/pain, fatigue, headache, dyspnea, anosmia and ageusia.
Tao et al, 2020 [14]	Weibo	15,900 posts	December 31, 2019, to March 16, 2020	Analysis of oral health–related information posted on Weibo revealed home oral care and dental services to be the most common tweet topics.
Wahbeh et al, 2020 [15]	Twitter	10,096 tweets from 119 medical professionals	December 1, 2019, to April 1, 2020	Identified eight themes: actions and recommendations, fighting misinformation, information and knowledge, the health care system, symptoms and illness, immunity, testing, and infection and transmission.
Budhwani et al, 2020 [16]	Twitter	193,862 tweets by US-based users	March 9 to March 25, 2020	Identified a large increase in the number of tweets referencing “Chinese virus” or “China virus.”
Rufai and Bunce, 2020 [17]	Twitter	203 viral tweets by 8 G7b world leaders	November 17, 2019, to March 17, 2020	Identified three categories of themes: informative, morale-boosting, and political.
Park et al, 2020 [18]	Twitter	43,832 users and 78,233 relationships	Few weeks before February 29, 2020	Assessed speed of information transmission in networks and found that news containing the word “coronavirus” spread faster.
Lwin et al, 2020 [19]	Twitter	20,325,929 tweets from 7,033,158 users	January 28 to April 9, 2020	An examination of four emotions (fear, anger, sadness, and joy) revealed that emotions shifted from fear to anger, while sadness and joy also surfaced.
Pobiruchin et al, 2020 [20]	Twitter	21,755,802 tweets from 4,809,842 users	February 9 to April 11, 2020	Examined temporal and geographical variations of COVID-19–related tweets, focusing on Europe, and the categories and origins of shared external resources.

^aN/A: not applicable.

^bG7: Group of Seven.