Abstract
The purpose of this study was to demonstrate the use of social network analysis to understand public discourse on Twitter around the novel coronavirus disease 2019 (COVID-19) pandemic. We examined different network properties that might affect the successful dissemination by and adoption of public health messages from public health officials and health agencies. We focused on conversations on Twitter during 3 key communication events from late January to early June of 2020. We used Netlytic, a Web-based software that collects publicly available data from social media sites such as Twitter. We found that the network of conversations around COVID-19 is highly decentralized, fragmented, and loosely connected; these characteristics can hinder the successful dissemination of public health messages in a network. Competing conversations and misinformation can hamper risk communication efforts in a way that imperil public health. Looking at basic metrics might create a misleading picture of the effectiveness of risk communication efforts on social media if not analyzed within the context of the larger network. Social network analysis of conversations on social media should be an integral part of how public health officials and agencies plan, monitor, and evaluate risk communication efforts.
Highlights
We focused on 3 key communication events: (1) the World Health Organization (WHO)’s announcement of the novel coronavirus as a Public Health Emergency of International Concern (PHEIC) on January 30, (2) the WHO’s declaration of COVID-19 as a pandemic on March 11, and (3) the WHO’s updated assessment of the pandemic as a continued global threat on June 8, after surpassing 7 million cases and 400,000 deaths worldwide
Communication Event 1: WHO Declares the Novel Coronavirus a Public Health Emergency of International Concern One-hundred thousand tweets including “coronavirus” by 89,690 unique posters were collected from January 30, 2020, at 7:53 AM (AST) to January 31, 2020, at 8:54 AM (AST)
In this study, we used Social network analysis (SNA) to examine and understand public discourse on Twitter around 3 key announcements made by the WHO during the COVID-19 pandemic
Summary
The purpose of this study was to demonstrate the use of social network analysis to understand public discourse on Twitter around the novel coronavirus disease 2019 (COVID-19) pandemic. We examined different network properties that might affect the successful dissemination by and adoption of public health messages from public health officials and health agencies
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