关键词: 信息失真, 微博谣言, 系统动力学, 竞争传播模型, 网络空间治理

Abstract: Rumor informationon the internet is typically bad information generated by information distortion. As with the expansion of social network users, the governance of bad information on the internet has become an important issue that needs to be addressed urgently.
Therefore, taking the Weibo rumor event as a specific research object, the competitive dissemination process of rumor information and repelling information is focused on. Six factors related to the competitive dissemination process are explored: the dissemination rate of rumor information β₁,the dissemination rate of repelling information β₂,one-way replacement rate θ,the effective contact weight of rumor information dissemination process w_A, the effective contact weight of repelling informationdissemination process w_B, the effective contact weight of one-way replacement processes w_C.Studies on targeted regulation of such factors are carried out and governance policies on internet bad information are designed.
Based on literature and empirical research, the SIR infectious disease model is used and improved in this paper. The six factors described above are included in the model to incorporate the effects of user literacy and network contact environment. Combined with the mean field theory, the competitive dissemination model of rumor events is established from the perspective of system dynamics by mathematical modeling method.The model simulation method can visualize abstract mathematical equations. Anylogic simulation modeling tool is therefore used to carry out simulation experiments in this paper. Six situations of competitive dissemination of rumor information and repelling information are simulated. The influences of different parameters on the competitive dissemination process are fully revealed through simulation experiments and parameter sensitivity analysis.
After analysis,the one-way replacement relationship between user states is found and is added in the simulation experiments. The experiments show that β₂ and w_B are the key control factors. Flexible regulation of those indicators could help improve the effectiveness of bad information governance. Furthermore, policy suggestions to improve the network literacy of Internet users and to regulate the contact environment of network node through technical intervention are put forward.This paper uses Python to collect data of rumor cases publicly disclosed on Weibo in 2019-2020. After cleaning, data are selected for empirical analysis.
The competitive dissemination model proposed in this paper combines the key elements of previous researches in the field of bad information dissemination. The model is flexible and can meet the demand of factor-targeted analysis, providing a new idea for modeling and optimization of bad information communication. This model has strong practicability, it can fully simulate different competitive dissemination scenarios based on reality, and can provide better solutions for bad information governance.

Key words: information distortion, Weibo rumors, system dynamics theory, the competitive propagation model, cyberspace governance