Article ranking with location-based weight in contextual citation network

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-09-18 DOI:10.1016/j.joi.2024.101591
Jong Hee Jeon, Jason J. Jung
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引用次数: 0

Abstract

This paper proposes a method to evaluate academic impact that focuses on spatial context in which citations occur in sections of citing papers. Previous studies measured impact of papers using external factors such as journals, time, and authors. However, these methods overlooks context of citations, leading to problem of treating papers with same citation counts equivalently. To overcome this issue, we designed a citation network by reflecting on the spatial context in which cited papers are cited in the citing paper and measured their impact. Spatial context is defined by the specific section of the citing paper (Introduction, Method, Result, Discussion, Conclusion) where the citation appears. We collected 818 citing papers and 13,257 cited papers from 2013–2022 from Journal of Informetrics and constructed a context-reflected citation network. Further, we utilized CRITIC method and weighted PageRank algorithm for measuring section-specific weights and impact. Results obtained in this study suggest that the impact of cited papers varies significantly depending on the section context in which they appear. We use Kendall τ coefficient for analyzing correlation between “times cited” rankings and contextual PageRank. The Kendall τ coefficient between two ranks for entire dataset is 0.473. This study provides a multidimensional framework to assess the impact of academic papers, suggesting that future evaluations should consider not only the number of citations but also their context.

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在上下文引文网络中基于位置权重的文章排名
本文提出了一种评估学术影响力的方法,该方法关注引用论文章节中引文发生的空间环境。以往的研究使用期刊、时间和作者等外部因素来衡量论文的影响力。然而,这些方法忽略了引文的上下文,导致了同等引用次数的论文被等同对待的问题。为了克服这个问题,我们设计了一个引文网络,反映了被引论文在引文中被引用的空间背景,并测量了它们的影响。空间背景由引用论文中出现引文的具体章节(引言、方法、结果、讨论、结论)来定义。我们从《Journal of Informetrics》中收集了 2013-2022 年间的 818 篇引用论文和 13257 篇被引用论文,并构建了上下文反映的引用网络。此外,我们还利用 CRITIC 方法和加权 PageRank 算法来衡量特定章节的权重和影响力。研究结果表明,被引论文的影响力因其出现的章节背景不同而有很大差异。我们使用 Kendall τ 系数来分析 "被引次数 "排名与上下文 PageRank 之间的相关性。在整个数据集中,两个排名之间的 Kendall τ 系数为 0.473。本研究为评估学术论文的影响力提供了一个多维框架,建议未来的评估不仅要考虑引用次数,还要考虑其背景。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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