Network Analysis of the North American Skull Base Society Membership

北美颅底学会会员网络分析

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Abstract

Background  The membership of the North American Skull Base Society (NASBS) has grown considerably in recent years with diversity in subspecialty training, gender, and geography. The academic relationships and contributions of its membership have not been studied. Objectives  This study aimed to (1) measure academic contributions of NASBS membership; (2) identify influential nodes of academic collaboration; (3) identify opportunities for future collaboration and mentorship. Methods  Peer-reviewed publications of members of NASBS (2019 NASBS website) were identified using Scopus author name search. Network structures were constructed and analyzed using the graph-tool python library to produce a weighted coauthorship network and compute centrality measures. Visual network maps were then produced using Gephi network visualization software. Results  The coauthor network contained 952 members with found publications and 4,996 connections. A total of 846 (88.9%) members were contained in a single connected giant component; 102 members were unconnected, and 64 members had a single connection. Girvan-Newman clustering identified 267 communities, where 13 contained at least 1% of the total membership each. The three largest communities contained 23.3, 8.4, and 6.9% of members. There were 111 published members identified as women; 5.4% of women were unconnected versus 11.4% of men. Average publication count for women was 32.3 (standard deviation [SD] 38.5) versus 70.5 (SD 106) for men. Average citation count for women was 543 (SD 1,012) versus 1,389 (SD 2,893) for men. Conclusion  Network mapping of membership of the NASBS helps to visualize the academic activities and relationships of the NASBS and reveals areas of concentration and influence within the specialty.

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