NSLS: A Neighbor Similarity and Label Selection-Based Algorithm for Community Detection

Shihu Liu, Hui Chen (), Shuang Li and Xiyang Yang
Additional contact information
Shihu Liu: School of Mathematics and Computer Science, Yunnan Minzu University, Kunming 650504, China
Hui Chen: School of Mathematics and Computer Science, Yunnan Minzu University, Kunming 650504, China
Shuang Li: School of Mathematics and Computer Science, Yunnan Minzu University, Kunming 650504, China
Xiyang Yang: Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou Normal University, Quanzhou 362000, China

Mathematics, 2025, vol. 13, issue 8, 1-24

Abstract: Community detection is still regarded as one of the most applicable methods for discovering latent information in complex networks. Recently, many similarity-based community detection algorithms have been widely applied to the analysis of complex networks. However, these approaches may also have some limitations, such as relying solely on simple similarity measures, which makes it difficult to differentiate the tightness of the relation between nodes. Aiming at this issue, this paper proposes a community detection algorithm based on neighbor similarity and label selection (NSLS). Initially, the algorithm assigns labels to each node using a new local similarity measure, thereby quickly forming a preliminary community structure. Subsequently, a similarity parameter is introduced to calculate the similarity between nodes and communities, and the nodes are reassigned to more appropriate communities. Finally, dense communities are obtained by a fast-merge method. Experiments on real-world networks show that the proposed method is accurate, compared with recent and classical community detection algorithms.

Keywords: complex network; community detection; label selection; neighbor similarity (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/8/1300/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/8/1300/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:8:p:1300-:d:1635477

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().