基于节点亲密度和影响力的社交网络舆论形成模型

针对舆论传播过程中个体交互的广泛性和个体社会影响力的差异性，在Hegselmann-Krause模型的基础上建立了社交网络舆论形成模型。新模型通过引入个体间亲密度、人际相似性和交互强度等概念，对个体交互集合进行了扩展，并对影响力权重进行了合理量化，进而构建更切合实际的观点交互规则。通过一系列仿真实验，分析了模型主要参数在舆论演化中的作用。结果表明：在不同信任阈值下，群体观点均能收敛到一致，形成舆论共识；且信任阈值越大，收敛时间越短；当信任阈值为0.2时，收敛时间仅为10。同时，扩大交互集合、提高人际相似性的作用强度会促进舆论共识的形成。此外，当无标度网络的聚类系数和平均度较高时，群体观点更容易产生趋同效应。研究结果有助于理解舆论形成的动力学过程，对社会管理者进行决策分析具有指导作用。

Opinion formation model of social network based on node intimacy and influence

Aiming at the universality of individual interaction and the heterogeneity of individual social influence in opinion spreading, an opinion formation model of social network was proposed on the basis of Hegselmann-Krause model. By introducing the concepts of intimacy between individuals, interpersonal similarity and interaction strength, the individual interactive set was extended, the influence weight was reasonably quantified, and more realistic view of interaction rule was built. Through a series of simulation experiments, the effects of main parameters in the model on opinion evolution were analyzed. The simulation results indicate that group views can converge to the same and form consensus under different confidence thresholds. And the larger the confidence threshold is, the shorter the convergence time is. When confidence threshold is 0.2, convergence time is only 10. Meanwhile, extending the interactive set and increasing the strength of interpersonal similarity will promote consensus formation. Besides, when the clustering coefficient and the average degree of scale-free network are higher, the group views are more likely to produce convergence effect. The results are helpful to understand the dynamic process of opinion formation, and can guide social managers to make decisions and analysis.