Scientific impact analysis: Unraveling the link between linguistic properties and citations

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Informetrics Pub Date : 2024-03-29 DOI:10.1016/j.joi.2024.101526
Priya Porwal , Manoj H. Devare
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Abstract

The Scholar's success is indicated by the number of citations it received for its publication. Examining the correlation between the linguistic attributes of scholarly publications and their scientific influence holds significant importance. This study analyzed 1000 research papers by highly ranked authors from computer science and electronics backgrounds. The title, abstract, and conclusion sections of the paper were analyzed. This study utilizes readability, lexical diversity, lexical density, syntactic features, and coherence measures to establish the correlation between citations and the textual content of an article. The characteristics of the publication were evaluated in relation to its research impact, which was classified into two categories, high citations and low citations. Additionally, the influence of various aspects on citations was assessed through the utilisation of the negative binomial regression model, ordinary least square model, and spearman correlation. This analysis took into account the characteristics of length and structure. The results highlight a clear positive link between abstract readability, and number of references with increased citations. Additionally, each additional page contributes to a 0.2 % increase in citation count. However, the number of diagrams and conclusion readability show no significant connection with citations. Factors like title length, abstract length, and conclusion length also exhibit associations, though with slightly lower percentages. The results indicate that linguistic characteristics exert a limited impact on the acquisition of citations.

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科学影响分析:揭示语言特性与引文之间的联系
学者的成功与否取决于其出版物被引用的次数。研究学术出版物的语言属性与其科学影响力之间的相关性具有重要意义。本研究分析了 1000 篇由计算机科学和电子学背景的高排名作者撰写的研究论文。对论文的标题、摘要和结论部分进行了分析。本研究利用可读性、词汇多样性、词汇密度、句法特征和连贯性测量方法来确定引文与文章文本内容之间的相关性。根据研究影响力对出版物的特征进行了评估,并将其分为高引用和低引用两类。此外,还利用负二项回归模型、普通最小二乘法模型和矛曼相关法评估了各个方面对引用率的影响。这一分析考虑了篇幅和结构的特点。结果表明,摘要的可读性和参考文献的数量与引用次数的增加之间存在明显的正相关关系。此外,每增加一页,引用次数就会增加 0.2%。然而,图表数量和结论可读性与引用量没有明显联系。标题长度、摘要长度和结论长度等因素也有关联,但百分比略低。结果表明,语言特点对获得引用量的影响有限。
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来源期刊
Journal of Informetrics
Journal of Informetrics Social Sciences-Library and Information Sciences
CiteScore
6.40
自引率
16.20%
发文量
95
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.
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