{"title":"Article ranking with location-based weight in contextual citation network","authors":"Jong Hee Jeon, Jason J. Jung","doi":"10.1016/j.joi.2024.101591","DOIUrl":null,"url":null,"abstract":"<div><p>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 <em>τ</em> coefficient for analyzing correlation between “times cited” rankings and contextual PageRank. The Kendall <em>τ</em> 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.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101591"},"PeriodicalIF":3.4000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Informetrics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751157724001032","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
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.
期刊介绍:
Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.