<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Coronavirus disease of 2019 (COVID-19)’s devastating effects on the physical and mental health of the public are unlike previous medical crises, in part because of people’s collective access to communication technologies. Unfortunately, a clear understanding of the diffusion of health information on social media is lacking, which has a potentially negative impact on the effectiveness of emergency communication. This study applied social network analysis approaches to examine patterns of #COVID19 information flow on Twitter. A total of 1,404,496 publicly available tweets from 946,940 U.S. users were retrieved and analyzed. Particular attention was paid to the structures of retweet and mention networks and identification of influential users: information sources, disseminators, and brokers. Overall, COVID-19 information was not transmitted efficiently. Findings pointed to the importance of fostering connections between clusters to promote the diffusion in both networks. Lots of localized clusters limited the spread of timely information, causing difficulty in establishing any momentum in shaping urgent public actions. Rather than health and communication professionals, there was dominant involvement of non-professional users responsible for major COVID-19 information generation and dissemination, suggesting a lack of credibility and accuracy in the information. Inadequate influence of health officials and government agencies in brokering information contributed to concerns about the spread of dis/misinformation to the public. Significant differences in the type of influential users existed across roles and across networks. Conceptual and practical implications for emergency communication strategies are discussed.</p></abstract>

Coronavirus disease of 2019 (COVID-19)’s devastating effects on the physical and mental health of the public are unlike previous medical crises, in part because of people’s collective access to communication technologies. Unfortunately, a clear understanding of the diffusion of health information on social media is lacking, which has a potentially negative impact on the effectiveness of emergency communication. This study applied social network analysis approaches to examine patterns of #COVID19 information flow on Twitter. A total of 1,404,496 publicly available tweets from 946,940 U.S. users were retrieved and analyzed. Particular attention was paid to the structures of retweet and mention networks and identification of influential users: information sources, disseminators, and brokers. Overall, COVID-19 information was not transmitted efficiently. Findings pointed to the importance of fostering connections between clusters to promote the diffusion in both networks. Lots of localized clusters limited the spread of timely information, causing difficulty in establishing any momentum in shaping urgent public actions. Rather than health and communication professionals, there was dominant involvement of non-professional users responsible for major COVID-19 information generation and dissemination, suggesting a lack of credibility and accuracy in the information. Inadequate influence of health officials and government agencies in brokering information contributed to concerns about the spread of dis/misinformation to the public. Significant differences in the type of influential users existed across roles and across networks. Conceptual and practical implications for emergency communication strategies are discussed.

COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers

Connections

This work is licensed under the Creative Commons Attribution 4.0 International License.

Coronavirus disease of 2019 (COVID-19)’s devastating effects on the physical and mental health of the public are unlike previous medical crises, in part...

COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers

Publicado en línea: 05 ene 2021

Páginas: 129 - 142

DOI: https://doi.org/10.21307/connections-2019.018

Palabras clave
COVID, Information diffusion, Health communication, Social network analysis, Twitter

© 2020 Ian Kim et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers

Publicado en línea: 05 ene 2021

Páginas: 129 - 142

DOI: https://doi.org/10.21307/connections-2019.018

Palabras claveCOVID, Information diffusion, Health communication, Social network analysis, Twitter

© 2020 Ian Kim et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
COVID, Information diffusion, Health communication, Social network analysis, Twitter