基于期刊论文集的二部和一部加权网络的构建
Construction of bipartite and unipartite weighted networks from collections of journal papers
摘要：
这项工作提出了一个模型，允许研究专业通过专业的社会和认识论过程中的期刊论文集的表现形式。论文集被建模为连接7种类型实体的耦合二分网络。引入基于矩阵的链接权函数计算论文集的加权二部网络和加权单部共生网络。这些权重计算方法，当与未加权的二分增长模型结合使用时，在论文集中为加权网络生成简单的增长模型。
英文摘要：
This work presents a model that allows the study of research specialties through the manifestations of the specialty's social and epistemological processes in a collection of journal papers. Collections of papers are modeled as coupled bipartite networks interlinking 7 types of entities. Matrix-based link weight functions are introduced to calculate weighted bipartite networks and weighted unipartite co-occurrence networks in the collection of papers. These weight calculation methods, when used in conjunction with unweighted bipartite growth models, produce simple growth models for weighted networks in collections of papers.
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