A novel knowledge-based multi-population framework for studying opinion dynamics of migrated individuals

Sarvnaz Sadeghi, Pooya Moradian Zadeh
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Abstract

Many people around the world migrate to other places for a variety of reasons. As a result of social collaboration and knowledge exchange, their opinions about a topic can change over time. In this research, we propose a multi-population framework to track the dynamics of the opinion of a migrated individual in different scenarios. Each population is represented by a weighted graph and is associated with a belief space, which is a knowledge repository that stores the normative knowledge of that population. We also define different metrics to measure the level of change in an individual's opinion after migration. In our model, the social influence of each person is dependent on their own neighbors' opinions and acceptance rate, as well as the norms of the origin and destination societies. The results show that our proposed framework can capture the opinion dynamics in various settings and scenarios.
基于知识的迁移个体意见动态研究新框架
世界上许多人由于各种原因迁移到其他地方。由于社会协作和知识交换,他们对一个主题的看法可以随着时间的推移而改变。在这项研究中,我们提出了一个多种群框架来跟踪不同情景下迁移个体的意见动态。每个种群由加权图表示,并与信念空间相关联,信念空间是存储该种群规范知识的知识库。我们还定义了不同的度量来度量迁移后个人意见的变化程度。在我们的模型中,每个人的社会影响力取决于自己邻居的意见和接受率,以及来源国和目的地国社会的规范。结果表明,我们提出的框架可以捕捉到不同环境和场景下的意见动态。
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