Quantifying cohesion in high citation research article titles: a cross-disciplinary and diachronic investigation

IF 3.5 3区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Scientometrics Pub Date : 2024-08-01 DOI:10.1007/s11192-024-05123-y
Jiawei Wang
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Abstract

This study presents the result of a cross-disciplinary and diachronic examination of cohesive devices used in high citation research article (HCRA) titles, a hitherto less-explored subgenre of academic discourse. Based on Halliday and Matthiessen’s (2014) Cohesion Model, the research analyzed the employment of connectors in a self-constructed corpus of 30,000 HCRA titles from disciplines of Biology, Chemistry, Linguistics, and Music from 1980 to 2023. Comparisons of disciplinary and diachronic changes of connectors were made in two-way multivariate analyses of variance (MANOVA), and follow-up analyses of variance (ANOVA). Major findings indicate that discipline, as compared to period, is the determinant of cohesion in HCRA titles, albeit in medium effect size. The use of Extension and Enhancement prevail HCRA titles, suggesting an exponential increase of sophistication and comprehensiveness of information in the curation and dissemination of scientific knowledge. Specifically, cohesion of HCRA titles is predominantly realized by additive, temporal, and causal connectors with sharp contrasts between soft and hard sciences, indicating longer titles with these connectors attract readers by harnessing their familiarity of disciplinary knowledge. Quantitative characterization of cohesion in HCRA titles shed light on how expert writers coherently organize titles to maximize informativeness and research impact, thereby contributing pedagogically to academic writing for English for Academic and Specific Purposes, and empirically for the research on the predictability of citation impacts.

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量化高引用率研究文章标题中的内聚力:跨学科和非同步调查
高引用率研究文章(HCRA)是迄今为止较少被探索的学术话语亚类型,本研究介绍了对高引用率研究文章(HCRA)标题中使用的连贯手段进行跨学科和异时空研究的结果。研究以 Halliday 和 Matthiessen(2014 年)的内聚力模型为基础,分析了自建语料库中连接词的使用情况,该语料库包含从 1980 年到 2023 年生物、化学、语言学和音乐等学科的 30,000 篇高被引研究文章标题。通过双向多变量方差分析(MANOVA)和后续方差分析(ANOVA)对连接词的学科变化和异时变化进行了比较。主要研究结果表明,与时期相比,学科是《人类成果评估》标题凝聚力的决定因素,尽管其效应大小为中等。扩展和增强 "在 HCRA 标题中的使用占了上风,这表明在科学知识的整理和传播过程中,信息的复杂性和全面性呈指数增长。具体来说,HCRA 标题的内聚力主要是通过加法、时间和因果连接词实现的,软科学和硬科学之间的对比鲜明,这表明使用这些连接词的长标题可以利用读者对学科知识的熟悉程度来吸引读者。对HCRA标题中内聚力的定量表征揭示了专家写作者如何连贯地组织标题以最大限度地提高信息量和研究影响力,从而在教学上有助于学术英语和特定用途英语的学术写作,在实证上有助于引文影响力可预测性的研究。
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来源期刊
Scientometrics
Scientometrics 管理科学-计算机:跨学科应用
CiteScore
7.20
自引率
17.90%
发文量
351
审稿时长
1.5 months
期刊介绍: Scientometrics aims at publishing original studies, short communications, preliminary reports, review papers, letters to the editor and book reviews on scientometrics. The topics covered are results of research concerned with the quantitative features and characteristics of science. Emphasis is placed on investigations in which the development and mechanism of science are studied by means of (statistical) mathematical methods. The Journal also provides the reader with important up-to-date information about international meetings and events in scientometrics and related fields. Appropriate bibliographic compilations are published as a separate section. Due to its fully interdisciplinary character, Scientometrics is indispensable to research workers and research administrators throughout the world. It provides valuable assistance to librarians and documentalists in central scientific agencies, ministries, research institutes and laboratories. Scientometrics includes the Journal of Research Communication Studies. Consequently its aims and scope cover that of the latter, namely, to bring the results of research investigations together in one place, in such a form that they will be of use not only to the investigators themselves but also to the entrepreneurs and research workers who form the object of these studies.
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