主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院

   

Research on the Evolution Mechanism of Weibo Users Discussion Heat for Public Demand Response Policies-- A case based on Weibo user data

Qi Mingliang Qi   

  1. , 100190,
  • Received:2025-03-29 Revised:2025-08-02 Accepted:2025-11-19
  • Contact: Qi, Qi Mingliang

Abstract: In the new media era, policies responding to public demands can be disseminated to the public immediately, yet they require time to be implemented and demonstrate effectiveness. Research on the evolution mechanism of public discussion heat regarding related topics aids administrative departments in assessing public opinion trends and guiding discussion heat proactively and appropriately.When Weibo users become aware of government-published policies addressing public demands, their desire for immediate gratification motivates them to expect benefits from these policies. Concurrently, users possess self-regulation capabilities, which exert a counteracting influence on their immediate gratification impulses. Additionally, users tend to forget previously viewed content, thereby influencing their online browsing behaviors and relational dynamics.Weibo users were categorized into four groups: Unknowns, Followers, Communicators, and Silencers. By incorporating the psychological factors of immediate gratification and self-regulation, transition functions between these groups were established, forming a dissemination model based on immediate gratification and self-regulation.The dataset comprised 119,057 Weibo comments from 90,705 users under relevant topics on the Sina Weibo platform during the implementation of the "Nine Prohibitions" policy. Genetic algorithms were subsequently employed to fit the model parameters, reconstructing the temporal evolution curve of user participation in related discussions.Finally, the impact of parameters on the scale and growth rate of discussion heat was analyzed from two dimensions: information dissemination pathways and user psychology. The effects of four moderation strategies on discussion heat were evaluated. Findings indicate that the model effectively explains the evolutionary trend of potential maximum discussion heat among Weibo users. Measures such as labeling misinformation on social media platforms and ly responding to public demands demonstrated relatively superior moderation efficacy. Future research could integrate additional psychological theories to better characterize the evolution of online public opinion.