融合社交网络用户自身属性的信息传播数学建模与舆情演化分析

针对传统的社交网络信息传播模型极少将用户属性和信息特征这两个因素纳入到信息传播模型研究中的不足,该文提出了一种基于用户自身属性的信息传播模型。首先该文抽取用户影响力、用户态度、用户年龄、信息能量、信息价值等特征并构建交互规则;其次,根据这些特征建立信息传播的数学模型,模拟社交网络舆情演化过程;最后,为验证模型的有效性,开展了与真实事件的实证分析对比实验。实验结果表明: 仿真结构与真实数据的相似度大于0.97,因而该模型符合社交网络舆情信息传播的特性,能够较为准确地描述社交网络中的舆情传播过程。

Mathematical Modeling and Public Opinion Evolution Analysis of Information Diffusion with the User Attributes

Most of the existing information diffusion models in online social network (OSN) are focused on the network structure, with little attention on the influence of user attributes and information characteristics. This paper proposes an information diffusion model based on user attributes. Firstly, this paper extracts the characteristics of user influence, user attitude, user age, information energy, information value, and then constructs interaction rules. Secondly, a mathematical model of information diffusion is established to simulate the evolution of public opinion in social networks based on these characteristics. Finally, in order to verify the effectiveness of the proposed model, empirical analysis and comparison experiments with real online social network events are carried out, revealing a similarity between the simulation structure and real data beyond 0.97.