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Julio-agosto de 2021, vol. 30, núm. 4
Interacción y visualización / Interaction and visualization

Discussion, news information, and research sharing on social media at the onset of Covid-19

Hyejin Park; J. Patrick Biddix; Han Woo Park

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Abstract: Social media platforms provide valuable insights into public conversations. They likewise aid in understanding current issues and events. Twitter has become an important virtual venue where global users hold conversations, share information, and exchange news and research. This study investigates social network structures among Twitter users with regard to the Covid-19 outbreak at its onset and its spread. The data were derived from two Twitter datasets by using a search query, "coronavirus", on February 28th, 2020, when the coronavirus outbreak was at a relatively early stage. The first dataset is a collection of tweets used in investigating social network structures and for visualization. The second dataset comprises tweets that have citations of scientific research publications regarding coronavirus. The collected data were analyzed to examine numerical indicators of the social network structures, subgroups, influencers, and features regarding research citations. This was also essential to measure the statistical relationships among social elements and research citations. The findings revealed that individuals tend to have conversations with specific people in clusters regarding daily issues on coronavirus without prominent or central voice tweeters. Tweets related to coronavirus were often associated with entertainment, politics, North Korea, and business. During their conversations, the users also responded to and mentioned the U.S. president, the World Health Organization (WHO), celebrities, and news channels. Meanwhile, people shared research articles about the outbreak, including its spread, symptoms related to the disease, and prevention strategies. These findings provide insight into the information sharing behaviors at the onset of the outbreak.

Keywords: Covid-19; Coronavirus; Twitter; NodeXL; Altmetrics; Social media; Social networks; Social network structure; News information; Research sharing.