This study investigates the differential impacts of corrections, awareness prompts, and legal warnings on the endorsement of fact-checking information (through both “likes” and expressed support in associated comments) across three types of misinformation motivation (dread, wedge-driving, wish) on Weibo, a major Chinese social media platform. Through manual labeling and BERT (a pretrained large language model), we analyzed a cleaned dataset of 4,942 original fact-checking Weibo posts from 18 November 2010 to 31 May 2022, created or shared by Weibo Piyao. Results indicate that government posts or those with visual cues received fewer “likes” but garnered more supportive comments, while awareness prompts and legal warnings received more supportive comments across three misinformation types. This research provides valuable insights into the practice of fact-checking on social media, highlighting how different strategies may vary in their impact depending on the nature of the misinformation being addressed.
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