Social media functions as a convenient source of information in dangerous situations. Social media has been criticized often amid the current coronavirus disease (COVID-19) pandemic, mainly due to their use as a medium for the quick spread of fake news, but no systematic research has yet been conducted on this issue. Mass infection occurred in Korea due to a closed religious group called Shincheonji in the greater Daegu metropolitan city, the fourth largest city in Korea. At the end of February 2020, the virus was spreading in South Korea following its initial outbreak in China, making Korea the new center of global attention. SARS-CoV-2 (severe acute respiratory coronavirus 2) is spreading rapidly around the world, and the number of associated deaths has also been increasing. Social media network analytics cannot replace the work of public health officials however, monitoring public conversations and media news that propagates rapidly can assist public health professionals in their complex and fast-paced decision-making processes. Nevertheless, the spillover effect of the news articles that delivered medical information about COVID-19 was greater than that of news with nonmedical frames. Tweets containing medically framed news articles (mean 7.571, SD 1.988) were found to be more popular than tweets that included news articles adopting nonmedical frames (mean 5.060, SD 2.904 N=40, P=.03, 95% CI 0.169-4.852).Ĭonclusions: Most of the popular news on Twitter had nonmedical frames.
The news frames used in the top sources were similar across the networks ( P=.89, 95% CI 0.004-0.006). There was a significant difference in the use of nonportal (n=14) and portal news (n=26) sites between the four network types.
Ethical issues such as deviant behavior among the population and an entertainment frame highlighting celebrity donations also emerged often. Many of the news items highlighted the positive roles being played by individuals and groups, directing readers’ attention to the crisis. The spread of information was faster, and the diameter value was lower than for those who used other terms. People who used the word “Coronavirus” communicated more frequently with each other. Results: The network analysis suggests that the spread of information was faster in the Coronavirus network than in the other networks (Corona19, Shincheon, and Daegu). Lastly, we conducted a content analysis of news frames used in the top-shared sources. Next, we classified top news channels shared via tweets. This study comparatively investigates how COVID-19-related issues have circulated on Twitter through network analysis. We generated four networks in terms of key issues regarding COVID-19 in Korea. Our final sample comprised of 43,832 users and 78,233 relationships on Twitter. Methods: Korean COVID-19-related Twitter data were collected on February 29, 2020. The real time aggregation of social media data can serve as a starting point for designing strategic messages for health campaigns and establishing an effective communication system during this outbreak. This study investigates information transmission networks and news-sharing behaviors regarding COVID-19 on Twitter in Korea. Objective: Few infodemiology studies have applied network analysis in conjunction with content analysis. Social media functions as a convenient source of information in pandemic situations. The role of social media amid the current coronavirus disease (COVID-19) pandemic has often been criticized, but little systematic research has been conducted on this issue.
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