A Generalized Modularity for Computing Community Structure in Fully Signed Networks. (24th February 2023)

• Record Type: Journal Article
• Authors: He, Xiaochen; Zhang, Ruochen; Zhu, Bin
• Other Names: Cherifi Hocine Academic Editor.
• Is Part Of: Complexity. Volume 2023(2023)
• Publication Date: 2023-02-24
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2023/8767131
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : The community structure in fully signed networks that considers both node attributes and edge signs is important in computational social science; however, its physical description still requires further exploration, and the corresponding measurement remains lacking. In this paper, we present a generalized framework of community structure in fully signed networks, based on which a variant of modularity is designed. An optimization algorithm that maximizes modularity to detect potential communities is also proposed. Experiments show that the proposed method can efficiently optimize the objective function and perform effective community detection.