关于“统计学家的共同引用和合作网络”的讨论

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
J. Loyal, Yuguo Chen
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引用次数: 0

摘要

我们要祝贺作者们发表了一篇引人入胜的文章,其中包含了深刻的分析,以及他们在管理高质量的共同引用和共同作者网络方面所做的辛勤工作。仅这些数据集就对统计学专业做出了宝贵贡献,这无疑将激励未来的数据科学项目和方法论进步。事实上,我们渴望在自己的课堂和研究中使用这些网络。此外,作者使用这些网络来解决网络科学中令人兴奋的问题,这些问题超出了人们熟悉的边缘插补和预测节点标签的问题。在这样做的过程中,作者进行了出色的分析,并采用了令人兴奋的新方法。这一分析是理解这些网络的第一步,本文提出的想法肯定会引发许多进一步的研究问题。对于如何影响研究或者,
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discussion of “Co-citation and Co-authorship Networks of Statisticians”
We want to congratulate the authors on a fascinating article containing an insightful analysis and their hard work curating the high-quality co-citation and co-authorship networks. These datasets alone are a valuable contribution to the statistics profes-sion, which will undoubtedly inspire future data science projects and advances in methodology. In fact, we are eager to use these networks in our own classrooms and research. Furthermore, the authors use these networks to tackling exciting questions in network science that go beyond the familiar problems of edge imputation and predicting node labels. In doing so, the authors perform a terrific analysis accompanied by exciting new methodology. This analysis serves as a great first step in understanding these networks, and the ideas initiated in this article will certainly stimulate many further research questions. For how do influence the research Or,
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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