双向持票观点动力学中的一致性、两极化和多样性
Consensus, Bi-polarization and Multiformity in Opinion Dynamics with Bidirectional Thresholds
摘要：
许多经验网络本质上是多元的，相互作用发生在任意代理人的群体中。然后，网络中的代理可以受到邻居类型的影响，常见的例子包括相似性，对立性和可忽略性。虽然在现实世界的复杂系统中，邻里之间的影响力可以准确地描述为一种既友好又敌对的关系，并且研究不同类型影响力下舆论演化的动态过程是有价值的，但很少有研究涉及这一问题。在本文中，我们开发了一个新的模型，在网络上的代理商与双向有界阈值的观点动力学的演变研究。我们定义了个体同化和排斥的范围，以识别不同类型的邻居，并通过转换意见差异来计算相应的邻居对个体的影响。仿真结果表明，该机制能有效解释意见演化过程中两极化现象的形成，双向有界阈值的设置对意见的最终分布有显著影响.此外，我们探讨了初始条件和小世界网络的结构对意见演化的影响。
英文摘要：
Many empirical networks are intrinsically pluralistic, with interactions occurring within groups of arbitrary agents. Then the agent in the network can be influenced by types of neighbors, common examples include similarity, opposition, and negligibility. Although the influence of neighbors can be described as an amicable and antagonistic relationship in complex real-world systems accurately, and the research on the dynamic process of public opinion evolution with different types of influence is valuable, few studies have mentioned that issue. In this paper, we develop a novel model on networks of agents with the bi-directional bounded thresholds for studying the evolution of opinion dynamics. We define the scope of individual assimilation and exclusion to identify different types of neighbors and calculate the impact of the corresponding neighbors on the individuals by converting the opinion difference. The simulation results show that the proposed mechanism can effectively explain the formation of bi-polarization during opinion evolution and the settings of the bi-directional bounded thresholds significantly influence the eventual distribution of opinions. Furthermore, we explore the impacts of the initial conditions and the structure of the small-world network on the evolution of opinions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
