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Co-authorship networks and scientific performance: an empirical analysis using the generalized extreme value distribution

机译:共同作者网络和科学绩效:使用广义极值分布的实证分析

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This paper aims to explore the effects of collaborative behaviour on scholar scientific performance. Individual network measures related to scholar centrality as well as attitude to collaborate with others are derived from co-authorship networks in a given scientific community (i.e. Italian academic statisticians). Co-authorship information have been collected from three data sources of national-based, discipline-based, and international-based high-impact publications. Both network and individual covariates are used to model individual h-index by generalized extreme value distribution. Results show a positive association between performance and actors' central position in the network. Having a large number of co-authors and occupying central positions are likely to positively affect scientific performance.
机译:本文旨在探讨合作行为对学者科学绩效的影响。与学者的中心性以及与他人合作的态度有关的个体网络测度是从特定科学界(即意大利学术统计学家)的共同作者网络得出的。共同作者信息是从基于国家,基于学科和基于国际的高影响力出版物的三个数据源中收集的。网络和个体协变量均用于通过广义极值分布对个体h指数进行建模。结果表明,表演与演员在网络中的中心地位之间存在正相关。拥有大量的合著者并占据中心位置很可能对科学绩效产生积极影响。

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