Exploring all-author tripartite citation networks: A case study of gene editing

Feifei Wang, Chenran Jia, Xiaohan Wang, Junwan Liu, Shuo Xu, Yang Liu and Chenyuyan Yang

Journal of Informetrics, 2019, vol. 13, issue 3, 856-873

Abstract: Constructing academic networks to explore intellectual structure realize academic community detection, which can promote scientific research innovation and discipline progress, constitutes an important research topic. In this study, tripartite citation is fused with co-citation and coupling relations as a way of weighting the strength of direct citations, and all-author tripartite citation networks were constructed due to the contributions of all authors to the resulting publications. For purpose of exploring the potential of the all-author exclusive and inclusive tripartite citation networks, gene editing is taken as a case study. The extensive experimental comparisons are conducted with the traditional author single-citation networks and first-author tripartite citation network in terms of network structure characteristics, identifying core scholars, and exploring intellectual structures. The following conclusions can be drawn as follows: our all-author tripartite citation networks are able to help identify the most influential scholars in the field of gene editing, and the intellectual structures from exclusive tripartite citation networks are optimal.

Keywords: Tripartite citation fusion; All-author counting; Intellectual structure; Gene editing (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:13:y:2019:i:3:p:856-873

DOI: 10.1016/j.joi.2019.08.002

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