On a Notion of Graph Centrality Based on L1 Data Depth

• 成果类型: Article; Early Access
• 署名作者: Kang, Seungwoo; Oh, Hee-Seok
• 署名单位: Seoul National University (SNU); Seoul National University (SNU)
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2025.2520467
• 发表日期: 2025
• 关键词: index

摘要

A new measure, L-1 centrality, is proposed to assess the centrality of vertices in an undirected and connected graph. The proposed measure can adequately handle graphs with weights assigned to vertices and edges. This study provides tools for graphical and multiscale analysis based on the L-1 centrality. Specifically, the suggested analysis tools include the target plot, L-1 centrality-based neighborhood, and local L-1 centrality. Most importantly, our work is closely associated with the concept of data depth for multivariate data, which allows for a wide range of practical applications of the proposed measure. Throughout this article, we demonstrate our tools with two interesting examples: the Marvel Cinematic Universe movie network and the bill cosponsorship network of the 21st National Assembly of South Korea. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.