A self-organized approach for detecting communities in networks

Collingsworth, Ben; Menezes, Ronaldo

doi:10.1007/s13278-014-0169-5

Cited by 7 publications

(1 citation statement)

References 24 publications

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“…Various clustering methods have been applied in research related to the classification problem in diverse fields. Clustering or community finding is a crucial and one of the most common tasks in the field of complex networks (Radicchi et al 2004;Palla et al 2005;Reichardt and Bornholdt 2006;Boccaletti et al 2006;Rosvall and Bergstrom 2008;Gómez et al 2009;Collingsworth and Menezes 2014;Jia et al 2015;Duan et al 2021;Kuikka 2021;Kumar and Dohare 2021;Su et al 2021), where the topological structure of complex networks can be characterized by partitioning networks into densely connected subgraphs (Salter-Townshend et al 2012). Recognizing cohesive clusters or communities and their boundaries allows the classification of nodes according to their topological position in the network (Fortunato 2010;Piccardi et al 2010) or retaining the same properties.…”

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confidence: 99%

Cohesion and segregation in the value migration network: Evidence from network partitioning based on sector classification and clustering

Siudak

2023

Soc. Netw. Anal. Min.

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Cluster structure detection of the network is a basic problem of complex network analysis. This study investigates the structure of the value migration network using data from 499 stocks listed in the S&P500 as of the end of 2021. An examination is carried out whether the process of value migration creates a cluster structure in the network of companies according to economic activity. Specifically, the cohesion and segregation of the extracted modules in the network division according to (i) sector classification, (ii) community division, and (iii) network clustering decomposition are assessed. The results of this study show that the sector classification of the value migration network has a non-cohesive structure, which means that the flow of value in the financial market occurs between companies from various industries. Moreover, the divisions of the value migration network based on community detection and clustering algorithm are characterized by intra-cluster similarity between the vertices and have a strong community structure. The structure of the network division into modules corresponding to the classification of economic sectors differs significantly from the partition based on the algorithms applied.

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