Rumors, Fakes and Fact-checking in Chinese Social Media: The Case of WeChat

This research examines the typology of rumors and fact-checking mechanisms in Chinese social media, focusing on the WeChat platform. The study analyzes 300 cases of disinformation extracted from the "Rumor Refutation Assistant" application in WeChat between 2023 and 2025 using Python-based tools.The author investigates the structural and content characteristics of rumors, their thematic classification across various categories (healthcare, public safety, and others), and both institutional and user-driven verification strategies. Special attention is given to the relationship between rumor types and fact-checking mechanisms' effectiveness within China's . The methodology includes content analysis for fakes typology, text mining techniques (TF-IDF, LDA), and social network analysis to examine information dissemination patterns. Findings reveal significant patterns in fakes distribution, where algorithmic and institutional factors substantially influence information perception. Healthcare-related messages (39.67%), technology information (23.00%), and public safety content (21.33%) dominate the fakes landscape. The author's contribution lies in analyzing information verification mechanisms within Chinese social media and identifying correlations between fake typologies and refutation strategies' effectiveness. The research novelty stems from examining rumor typology and fact-checking in the Chinese context, emphasizing WeChat's role in information dissemination. The study demonstrates that mitigating disinformation requires AI integration, active user participation in fact-checking, and effective legal regulation of the information space.

rumor, fact-checking, social media, WeChat, disinformation, information verification, China, mass media, debunking rumors, discursive Strategies