基于时序网络的舆情传播模型
Opinion Propagation Model Based on Temporal Networks
DOI: 10.12677/orf.2025.152092, PDF,    国家社会科学基金支持
作者: 吴韵梅：北京邮电大学数学科学学院，北京；张艺澎：威斯康星大学麦迪逊分校数学系，美国 麦迪逊
关键词: 社交网络；时序网络；基本再生数；舆情传播；SIR模型；Social Network； Temporal Network； Base Regeneration Number； Opinion Propagation； SIR Model
摘要: 移动通讯方式的发展带来了传播方式的转变，线上平台在实时发布消息的同时也提供了多种互动方式，网友的互动也为消息传播带来了不同程度的影响。研究带有时效和互动方式的时序网络能更好地还原线上传播过程，了解传播规律。本文结合SI1I2R模型考虑了互动方式对传播的影响，并运用活动驱动网络体现传播中的时序性，提出基于时序网络的舆情传播模型并进行理论分析。接着，结合该模型并分析时间步长对舆情传播的影响，发现时间步长对传播有比较显著的影响。最后，运用真实微博传播数据拟合模型数据并运用统计变量与经典SIR模型对比，证明模型的有效性。本文提出的模型也为线上舆情传播的分析提供了相关理论依据。
Abstract: The development of mobile communication methods has brought about a change in the mode of communication, and online platforms provide a variety of interactive ways while publishing news in real time, and the interaction of netizens has also brought varying degrees of influence to the dissemination of news. Studying the time series network with timeliness and interaction mode can better restore the online propagation process and understand the propagation law. In this paper, the influence of interaction mode on communication is considered in combination with the SI1I2R model, and the time-series mode of communication is reflected by using the activity-driven network, and the public opinion propagation model based on the time-series network is proposed and analyzed theoretically. Then, combined with the model, the influence of time step on public opinion propagation is analyzed, and it is found that time step has a significant impact on propagation. Finally, the model data was fitted using real Weibo propagation data, and the statistical variables were compared with the classic SIR model to demonstrate the effectiveness of the model. The model proposed in this paper also provides a relevant theoretical basis for the analysis of online public opinion propagation.
文章引用：吴韵梅, 张艺澎. 基于时序网络的舆情传播模型[J]. 运筹与模糊学, 2025, 15(2): 387-399. https://doi.org/10.12677/orf.2025.152092

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