Community detection on elite mathematicians' collaboration network

Huang, Yurui; Wang, Zimo; Tian, Chaolin; Ma, Yifang

2024-08-01

10.2478/jdis-2024-0026

JOURNAL OF DATA AND INFORMATION SCIENCE   影响因子和分区

2096-157X

2543-683X

Purpose This study focuses on understanding the collaboration relationships among mathematicians, particularly those esteemed as elites, to reveal the structures of their communities and evaluate their impact on the field of mathematics.Design/methodology/approach Two community detection algorithms, namely Greedy Modularity Maximization and Infomap, are utilized to examine collaboration patterns among mathematicians. We conduct a comparative analysis of mathematicians' centrality, emphasizing the influence of award-winning individuals in connecting network roles such as Betweenness, Closeness, and Harmonic centrality. Additionally, we investigate the distribution of elite mathematicians across communities and their relationships within different mathematical sub-fields.Findings The study identifies the substantial influence exerted by award-winning mathematicians in connecting network roles. The elite distribution across the network is uneven, with a concentration within specific communities rather than being evenly dispersed. Secondly, the research identifies a positive correlation between distinct mathematical sub-fields and the communities, indicating collaborative tendencies among scientists engaged in related domains. Lastly, the study suggests that reduced research diversity within a community might lead to a higher concentration of elite scientists within that specific community.Research limitations The study's limitations include its narrow focus on mathematicians, which may limit the applicability of the findings to broader scientific fields. Issues with manually collected data affect the reliability of conclusions about collaborative networks.Practical implications This study offers valuable insights into how elite mathematicians collaborate and how knowledge is disseminated within mathematical circles. Understanding these collaborative behaviors could aid in fostering better collaboration strategies among mathematicians and institutions, potentially enhancing scientific progress in mathematics.Originality/value The study adds value to understanding collaborative dynamics within the realm of mathematics, offering a unique angle for further exploration and research.

Greedy modularity maximization Infomap Collaboration network Community detection Mathematical awardees

ESCI

英语

第一 ; 通讯

National Natural Science Foundation of China["NSFC62006109","NSFC12031005"] ; The 13th Five-year plan for Education Science Funding of Guangdong Province["2021GXJK349","2020GXJK457"] ; Stable Support Plan Program of Shenzhen Natural Science Fund[20220814165010001]

Information Science & Library Science

Information Science & Library Science

WOS:001302208100001

SCIENDO

Web of Science

Southern Univ Sci & Technol, Dept Stat & Data Sci, Shenzhen 518055, Peoples R China

Huang, Yurui,Wang, Zimo,Tian, Chaolin,et al. Community detection on elite mathematicians' collaboration network[J]. JOURNAL OF DATA AND INFORMATION SCIENCE,2024.

Huang, Yurui,Wang, Zimo,Tian, Chaolin,&Ma, Yifang.(2024).Community detection on elite mathematicians' collaboration network.JOURNAL OF DATA AND INFORMATION SCIENCE.

Huang, Yurui,et al."Community detection on elite mathematicians' collaboration network".JOURNAL OF DATA AND INFORMATION SCIENCE (2024).