Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea.

BACKGROUND: SARS-CoV-2 (severe acute respiratory coronavirus 2) was spreading rapidly in South Korea at the end of February 2020 following its initial outbreak in China, making Korea the new center of global attention. 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. Social media functions as a convenient source of information in pandemic situations. OBJECTIVE: Few infodemiology studies have applied network analysis in conjunction with content analysis. This study investigates information transmission networks and news-sharing behaviors regarding COVID-19 on Twitter in Korea. 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. METHODS: Korean COVID-19-related Twitter data were collected on February 29, 2020. Our final sample comprised of 43,832 users and 78,233 relationships on Twitter. We generated four networks in terms of key issues regarding COVID-19 in Korea. This study comparatively investigates how COVID-19-related issues have circulated on Twitter through network analysis. Next, we classified top news channels shared via tweets. Lastly, we conducted a content analysis of news frames used in the top-shared sources. 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). People who used the word "Coronavirus" communicated more frequently with each other. The spread of information was faster, and the diameter value was lower than for those who used other terms. Many of the news items highlighted the positive roles being played by individuals and groups, directing readers' attention to the crisis. Ethical issues such as deviant behavior among the population and an entertainment frame highlighting celebrity donations also emerged often. There was a significant difference in the use of nonportal (n=14) and portal news (n=26) sites between the four network types. The news frames used in the top sources were similar across the networks (P=.89, 95% CI 0.004-0.006). 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). CONCLUSIONS: Most of the popular news on Twitter had nonmedical frames. Nevertheless, the spillover effect of the news articles that delivered medical information about COVID-19 was greater than that of news with nonmedical frames. 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.

Calling for justice with #JusticeforBreonnaTaylor: a case study of hashtag activism in the evolution of the black lives matter movement.

Taking a stage-based approach, before and after the release of the 15-h audio recording files of the grand jury's inquiry on the Breonna Taylor case on October 2, 2020, this study examined the #JusticeforBreonnaTaylor Twitter networks. By employing multimethodology, including natural language processing, social network analysis, and qualitative textual analysis, I examined keys connectors of the two Twitter networks and investigated major themes conducting thematic analysis of network discourses and highly associated hashtags with the hashtag #JusticeforBreonnaTaylor. In both networks, several key stakeholders, such as Benjamin Crump, Danial Cameron, and Black women activists were identified as key connectors along with social activists and ordinary participants. Demanding justice to the case was the core agenda of the hashtag activism. The findings of the study revealed that the participants not only shared breaking news and important information but also organized protests and routinely tagged people to spread messages about the Taylor's case on Twitter. The participants conversed major issues about the Taylor case and set the agendas for the next action, such as encouraging to take part in voting for the 2020 presidential election. The thematic analysis concurrently demonstrated that the network participants strongly demanded legal prosecution to the three Louisville cops that involved in the act of killing Breonna Taylor during the botched raid in her apartment.

Delving into Data Science Methods in Response to the COVID-19 Infodemic.

The circulation of myriad of information from diverse digital platforms during the COVID-19 pandemic caused the unprecedented infodemic. Along with the increased case numbers, the shared information accelerated exponentially, especially via social media, and a large proportion of the daily distributed information was blended with myth, rumors, pseudoscience, or modified facts. Uncovering viral mis- and disinformation narratives and information voids is essential to a swift and effective response on delivering public health information and policy by the governments during a public health emergency. Although many studies have examined how information was circulated and shared during the COVID-19 pandemic era, large gaps in literature exist as to how effectively to track, describe, and answer it. In this panel, the panelists propose and discuss data science methods to analyze the COVID-19 infodemic. We hope our panel contribute to exploring more effective and applicable data science methods to investigate infodemic in crises.

COVID-19 in the Twitterverse, from epidemic to pandemic: information-sharing behavior and Twitter as an information carrier.

In this study, we defined a Twitter network as an information channel that includes information sources containing embedded messages. We conducted stage-based comparative analyses of Twitter networks during three periods: the beginning of the COVID-19 epidemic, the period when the epidemic was becoming a global phenomenon, and the beginning of the pandemic. We also analyzed the characteristics of scientific information sources and content on Twitter during the sample period. At the beginning of the epidemic, Twitter users largely shared trustworthy news information sources about the novel coronavirus. Widely shared scientific information focused on clinical investigations and case studies of the new coronavirus as the disease became a pandemic while non-scientific information sources and messages illustrated the social and political aspects of the global outbreak, often including emotional elements. Multiple suspicious, bot-like Twitter accounts were identified as a great connector of the COVID-19 Twitterverse, particularly in the beginning of the global crisis. Our findings suggest that the information carriers, which are information channels, sources, and messages were coherently interlocked, forming an information organism. The study results can help public health organizations design communication strategies, which often require prompt decision-making to manage urgent needs under the circumstances of an epidemic.

Network typology, information sources, and messages of the infodemic twitter network under COVID-19.

During the COVID-19 crisis, fake news, conspiracy theories, and backlash against specific groups emerged and were largely diffused via social media. This phenomenon has been described as an "infodemic," and this study examined that the characteristics of infodemic on Twitter. Typological attributes of the infodemic Twitter network presented the features of "community clusters." The frequently shard domains and URLs demonstrated coherent characteristics within the network. Top domains and URLs were trustworthy information sources, popular blogs, and public health research institutions. Interestingly, the most shard conversational content of the network was a COVID-19 relevant incident occurred at a church in Korea based on misinformation and false belief.