论文标题
建模意见动力学：对异质种群的排名
Modeling Opinion Dynamics: Ranking Algorithms on Heterogeneous Populations
论文作者
论文摘要
影响过程的异质性是社会系统的重要特征：我们如何感知社会影响力以及我们如何影响其他人受到我们的意见和非公开属性的影响。后者包括人口，文化和结构（我们如何嵌入社交网络中）的特征。此外，影响过程的结果也可能取决于相互作用的个人在特征方面的相似性。本文解决了这个问题，并详细介绍了基于代理的模型，该模型对个人特征（无论是意见和非公开）敏感。该模型的排名算法强化了，该算法模仿了现实世界中的在线社交网络中广泛采用的排名算法。对于结果模型，我详细阐述了一个平均场近似值，该近似值通过普通微分方程的自主系统在宏观级别描述了模型的行为。该系统的属性进行了详尽的研究。
The heterogeneity of the influence processes is an important feature of social systems: how we perceive social influence and how we influence other individuals is heavily influenced by our opinion and non-opinion attributes. The latter include demographic, cultural, and structural (how we are embedded in social networks) characteristics. Furthermore, the results of the influence processes may also depend on how similar the interacting individuals are in terms of their features. This paper addresses this issue and elaborates on an agent-based model that is sensitive to the individual characteristics, both opinion and non-opinion ones. The model is fortified with a ranking algorithm that mimics the ranking algorithms widely adopted in real-world online social networks. For the resulting model, I elaborate a mean-field approximation that describes the behavior of the model at the macroscopic level via an autonomous system of ordinary differential equations. The properties of this system are thoroughly studied.
