Analysis of the Retweet Mechanism of Social Media—Based on Topic Filtering and Causal Inference
Recognizing the primary factors that influence information diffusion on social media platforms holds significant importance in the containment of harmful information spread.Previous research has primarily utilized regression analysis to identify variables that have a significant impact on retweets.However,these ap-proaches have been limited in terms of interpretability.Using statistical modeling and causal inference,this study analyzes the variables that affect retweets from user and text features.Subsequently,the dose-response function is generated to elucidate the causal relationship of the text sentiment to retweets.Additionally,considering the potential collection bias in observed social media datasets,this study uses topical clustering for data filtration.In the experimental analysis of Twitter dataset related to the Vaccine discussion and presidential election,we have identified the variables that impact the retweets,and investigated the causal impact of text sentiment to retweets.
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