CSFI for Social Media: Understanding and Predicting Cross-Community Information Propagation

Social platform users are intricately interconnected, forming a complex social system. Personalized recommendations help users access information from diverse sources, fostering community communication. Micro-level dynamic analysis technology offers a scientific approach to measuring and predicting information transmission. While fundamental dissemination principles are studied, cross-community communication scenarios are under-researched. This study presents a community-centric communication dynamics model (CSFI) to explain information transmission within and across communities on social media. Tested on Sina Weibo data, the model improves retweet prediction accuracy by 11.3 % over baselines. Accurately predicting information propagation on social media is crucial for public opinion analysis. This research aids in predicting dissemination trajectories, reflecting public sentiment, and guiding targeted information strategies or interventions.