论文部分内容阅读
以多层网络理论为基础,文章将社会集群行为置于线上社会网络和线下物理接触网络的混合结构中进行研究,归纳总结节点的异质性和社会关系的多样性,建立网络集群行为与现实社会集群行为的互动关系,建立社会集群行为的演化模型并通过计算实验方法进行验证。实验结果表明:社会个体之间的意见交换能够显著驱动社会集群行为;线上线下社会网络之间的互动更容易催生社会集群行为的涌现;社会个体的行为决策影响社会集群行为的涌现,社会个体之间的意见融合比意见分裂更容易催生社会集群行为的涌现。本文以新的视角和社会学领域新兴的计算实验方法研究社会集群行为,适应了社会集群行为结构多层化、个体异质化、关系多样化的新趋势,是对现有社会集群行为研究的有力拓展。
Based on the theory of multi-layer network, this paper studies the social cluster behavior in the mixed structure of online social network and offline physical contact network, sums up the heterogeneity of nodes and the diversity of social relations, and establishes the network cluster behavior And the social interaction of the actual behavior of the community to establish the evolution of social cluster behavior model and verified by computational experiments. The experimental results show that the exchange of opinions among social individuals can significantly drive social cluster behavior. The interaction between online and offline social networks is more likely to lead to the emergence of social cluster behavior. The behavior decision of social individuals affects the emergence of social cluster behavior. It is easier for opinion fusion than for opinion division to promote the emergence of social clustering behavior. In this paper, we study the behavior of social clusters with new perspectives and new computational experiments in the field of sociology, and adapt to the new trend of multi-stratification, individual heterogeneity and diversified relations of social cluster behavioral structures. Strong expansion.