arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2008.04647cs.DLphysics.soc-ph
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利用机构-引文网络测量机构和论文的影响力

Measure the Impact of Institution and Paper via Institution-citation Network

Xiaomei Bai, Fuli Zhang, Jin Ni, Lei Shi, Ivan Lee

摘要:

本文基于异质性的机构-引文网络,考察了机构和论文的影响力。引入了一个新的模型IPRank,同时衡量机构和论文的影响。该模型利用异质结构测度方法揭示了机构和论文的影响,反映了引文、机构和结构测度的影响。该模型首先基于美国物理学会(APS)数据集构建了一个异构的机构-引文网络,并对该网络的性能进行了评价。随后,PageRank被用来量化机构和论文的影响。最后,合并同一机构的影响力,计算机构和论文的排名。实验结果表明,IPRank模型可以更好地识别诺贝尔奖获得者所在的大学,表明所提出的技术可以很好地反映有影响力的研究。

英文摘要:

This paper investigates the impact of institutes and papers over time based on the heterogeneous institution-citation network. A new model, IPRank, is introduced to measure the impact of institution and paper simultaneously. This model utilises the heterogeneous structural measure method to unveil the impact of institution and paper, reflecting the effects of citation, institution, and structural measure. To evaluate the performance, the model first constructs a heterogeneous institution-citation network based on the American Physical Society (APS) dataset. Subsequently, PageRank is used to quantify the impact of institution and paper. Finally, impacts of same institution are merged, and the ranking of institutions and papers is calculated. Experimental results show that the IPRank model better identifies universities that host Nobel Prize laureates, demonstrating that the proposed technique well reflects impactful research.

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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