[1M1-OS-20a] 社会現象とAIと可視化(1/3)

[1M1-OS-20a-05] A Comparison of Flow-Aware and Non-Flow-Aware Community Detection Methods on COVID-19 Vaccine-Related Retweet Network

〇Hiromu Murakami¹, Yasuhiro Hashimoto¹ (1. The University of Aizu)

Keywords:COVID-19, twitter, network, community detection, visualization

Under the pandemic of COVID-19, a variety of right and wrong information is being spread on social media, causing confusion among users. Recently, a series of studies has been conducted to explore the mechanism behind the spread of disinformation and misinformation by discovering the community structure of the network created by message forwarding called retweeting on Twitter. In this study, we compared the community detection method based on the direction of information flow with the conventional method for the retweet network related to the COVID-19 vaccine. However, the community structure obtained was similar in both cases. This is not due to weak directionality of the network, but rather considered to be due to the synchronization of the edge weights and the pathways that exist within a group.