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arXiv 1807.04712cs.DLcs.SIphysics.soc-ph
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基于网络的科学绩效引文指标

A network-based citation indicator of scientific performance

Christian Schulz, Brian Uzzi, Dirk Helbing, Olivia Woolley-Meza

摘要:

科学家被嵌入到社会和信息网络中,这些网络影响着他们的科学工作质量、影响力以及他们所获得的认可,并受到这些网络的影响。在这里,我们量化了科学家在科学合作网络中的位置与他们收到的引用之间的系统关系。正如预期的那样,我们发现,在这个网络中,与其他人关系较近的作者平均被引用率高于与其他人关系较远的作者。我们构建了一个新的指标,S-指数,明确捕捉性能与网络位置沿两个互补的维度:预期性能由于网络位置和性能相对于这个位置。我们的方法的基础是代表一个作者的网络位置,通过他们的分布距离其他作者。然后,s指数对(1)个人网络位置相对于所有其他作者的引用潜力进行排名,以及(2)他们相对于具有可比网络位置的作者的引用量。通过这两个互补的维度来描述科学家的特征,可以用来在网络环境中做出更明智的评价。例如,它可以识别在传播科学思想方面发挥重要作用的个人。它还揭示了科学科学中的核心辩论,即作者团队的影响和跨科学领域的影响比较。

英文摘要:

Scientists are embedded in social and information networks that influence and are influenced by the quality of their scientific work, its impact, and the recognition they receive. Here we quantify the systematic relationship between a scientist's position in the network of scientific collaborations and the citations they receive. As expected, we find that authors closer to others in this network are, on average, more highly cited than those further away from others. We construct a novel indicator, the s-index, that explicitly captures performance linked to network position along two complimentary dimensions: performance expected due to network position and performance relative to this position. The basis of our approach is to represent an author's network position through their distribution of distances to other authors. The s-index then ranks (1) the citation potential of an individual's network position relative to all other authors, and (2) the citations they accrue relative to authors that have a comparable network position. Characterizing scientists through these two complimentary dimensions can be used to make more informed evaluations in a networked environment. For example, it can identify individuals that play an important role in diffusing scientific ideas. It also sheds a new light on central debates in the Science of Science, namely the impact of author teams and comparisons of impact across scientific fields.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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