Maximizing Closeness in Bipartite Networks: A Graph-Theoretic Analysis

Fazal Hayat and Daniele Ettore Otera ()
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Fazal Hayat: School of Mathematics and Statistics, Gansu Center for Applied Mathematics, Lanzhou University, Lanzhou 730000, China
Daniele Ettore Otera: Institute of Data Science and Digital Technologies, Vilnius University, 08412 Vilnius, Lithuania

Mathematics, 2024, vol. 12, issue 13, 1-13

Abstract: A fundamental aspect of network analysis involves pinpointing nodes that hold significant positions within the network. Graph theory has emerged as a powerful mathematical tool for this purpose, and there exist numerous graph-theoretic parameters for analyzing the stability of the system. Within this framework, various graph-theoretic parameters contribute to network analysis. One such parameter used in network analysis is the so-called closeness, which serves as a structural measure to assess the efficiency of a node’s ability to interact with other nodes in the network. Mathematically, it measures the reciprocal of the sum of the shortest distances from a node to all other nodes in the network. A bipartite network is a particular type of network in which the nodes can be divided into two disjoint sets such that no two nodes within the same set are adjacent. This paper mainly studies the problem of determining the network that maximize the closeness within bipartite networks. To be more specific, we identify those networks that maximize the closeness over bipartite networks with a fixed number of nodes and one of the fixed parameters: connectivity, dissociation number, cut edges, and diameter.

Keywords: closeness; bipartite graph; connectivity; dissociation number; diameter; cut edge (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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