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Structural centrality in fuzzy social networks based on fuzzy hypergraph theory

机译:基于模糊超图理论的模糊社交网络结构中心

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摘要

The knowledge of key network members is generally known to be critical to fuzzy social network analysis. Thus far, most studies aiming to identify critical members have taken network structural centrality measures. Since fuzzy graph cannot effectively depict the multidimensional relationships between the nodes of fuzzy social networks, a fuzzy social network model is developed complying with a mathematical theory of fuzzy hypergraph, allowing fuzzy social network to be represented more intuitively and visually. A fuzzy hypergraph model of fuzzy social network refers to a structure, vertex set acts as an object set, and the fuzzy relation in fuzzy relation structure is expressed by membership function and fuzzy relation matrix. With the fuzzy hypergraph model of fuzzy social networks, the definitions of structural centrality are given (i.e., degree centrality, relative degree centrality, closeness centrality, relative closeness centrality, betweenness centrality and relative betweenness centrality). Lastly, by analyzing examples, the process of building fuzzy social network with fuzzy hypergraph and the calculation method of centrality are illustrated.
机译:众所周知,关键网络成员的知识对于模糊社交网络分析至关重要。到目前为止,大多数旨在确定关键成员的研究都采取了网络结构中心措施。由于模糊图无法有效地描绘模糊社交网络的节点之间的多维关系,因此开发了一种模糊的社交网络模型,符合模糊超图的数学理论,允许模糊的社交网络更直观,视觉上表示更直观。模糊社交网络的模糊超图模型是指结构,顶点组用作对象集,模糊关系结构中的模糊关系由隶属函数和模糊关系矩阵表示。利用模糊社交网络的模糊超图模型,给出了结构中心的定义(即,度数中心,相对程度的中心,亲近的中心,相对闭合中心,相对的中心地位和相对的中心地位)。最后,通过分析示例,说明了用模糊超图构建模糊社交网络的过程和中心性的计算方法。

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