Asymmetric Decline Rather Than Backfire: A Repost-Network Analysis of Japanese Vaccine-Shedding Misinformation on X
This study investigates the diffusion of vaccine-shedding discourse on X in 2024, focusing on polarization in repost networks and reactions to corrective information. Here, "shedding" refers to the scientifically unsupported claim that harmful substances are released from individuals vaccinated against COVID-19 and cause adverse health effects in nearby unvaccinated people. Using 109,170 posts containing the Japanese term for "shedding" and 478,089 reposts collected from January 1 to December 31, 2024, we constructed a post-level repost network, identified discourse clusters, and examined changes in repost participation before and after major events. The results show that shedding discourse formed a two-pole structure consisting of pro-vaccine and anti-vaccine clusters. After news coverage denying shedding, we found no evidence of diffusion-level backfire in anti-vaccine repost activity. Instead, although the overall topic declined, repost participation in the anti-vaccine cluster decreased more sharply than that in the pro-vaccine cluster. User transition analysis further suggests that this change was not driven by the conversion of strongly anti-vaccine users, but by the entry of previously non-expressive users into pro-vaccine diffusion and the withdrawal of anti-vaccine supporters from repost activity. These findings suggest that corrective information may reshape the composition of misinformation diffusion participants without necessarily converting core opponents.