Examining the Most Popular Users in Twitter Covid-19 Conversations

Abstract

This paper discusses the structure of digital conversations about Covid-19 on Twitter. Social network analysis was adopted to examine the relationship structure amongst Twitter users engaged within the network of conversations, and what kind of content users communicate with each other. We collected 97.067 tweets since March 2020 until April 2021, then analyzed the tweet conversations using NodeXL software. The results show that the network of conversations was a low-density network with a low reciprocity vertex pairs ratio. This suggests that the conversations were not effectively built. The top-ten most popular actors engaged in the conversations were dominated by government institution accounts. There were also many mentions to popular accounts. However, popular actors did not actively respond to the conversations that ensued. These findings emphasize that during the global health crisis, which was characterized by uncertain situations, people were inclined to search for related information on a daily basis from authorities. Some users also mentioned suggestions to the authorities to share official information related to the constantly changing situations. This study also highlighted that Twitter was able to facilitate important conversations, because of its capability to distribute information widely and quickly.