How fast do scholarly papers get read by various user groups? A longitudinal and cross‐disciplinary analysis of the evolution of Mendeley readership

IF 2.8 2区 管理学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Zhichao Fang, Chonkit Ho, Zekun Han, Puqing Wu
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引用次数: 0

Abstract

To provide a dynamic perspective on the evolution of Mendeley readership, this study conducts an 8‐year longitudinal analysis of approximately 3.4 million scholarly papers published in 2015. Mendeley readership data were collected annually from 2016 to 2023 for the sampled papers to analyze the temporal accumulation patterns of readership following publication. The results indicate that Mendeley readership exhibits a speed advantage compared to citations and a prevalence advantage compared to Twitter mentions, demonstrating both initial prevalence and sustained growth on a yearly basis. However, the patterns of accumulation vary across disciplines, with papers in Biomedical and Health Sciences showing the fastest accrual of extensive Mendeley readership data. Leveraging demographic data provided by Mendeley, this study further investigates how different user groups—categorized by academic status, disciplinary affiliation, and geographic location—engage with papers across various disciplines. The findings highlight Mendeley readership as a rapid and substantial altmetric, yet they also emphasize the need to interpret the nature of the attention captured by Mendeley readership with caution, considering its potential biases introduced by the varying engagement levels of different user groups across disciplines.
不同用户群体阅读学术论文的速度如何?对 Mendeley 读者群演变的纵向和跨学科分析
为了从动态角度透视 Mendeley 读者群的演变,本研究对 2015 年发表的约 340 万篇学术论文进行了为期 8 年的纵向分析。从 2016 年到 2023 年,每年都会收集抽样论文的 Mendeley 读者数据,以分析论文发表后读者数量的时间积累模式。结果表明,与引用相比,Mendeley 读者数量具有速度优势,与推特提及相比,读者数量具有流行优势,表现出初始流行和逐年持续增长的特点。然而,不同学科的积累模式各不相同,生物医学和健康科学领域的论文显示出最快的广泛 Mendeley 读者数据积累速度。本研究利用 Mendeley 提供的人口统计数据,进一步调查了不同用户群体(按学术地位、学科归属和地理位置分类)如何与各学科论文打交道。研究结果凸显了 Mendeley 读者群是一个快速、可观的数据指标,但同时也强调了谨慎解释 Mendeley 读者群所捕捉的关注度的本质的必要性,因为不同学科的不同用户群的参与程度不同,可能会带来偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.30
自引率
8.60%
发文量
115
期刊介绍: The Journal of the Association for Information Science and Technology (JASIST) is a leading international forum for peer-reviewed research in information science. For more than half a century, JASIST has provided intellectual leadership by publishing original research that focuses on the production, discovery, recording, storage, representation, retrieval, presentation, manipulation, dissemination, use, and evaluation of information and on the tools and techniques associated with these processes. The Journal welcomes rigorous work of an empirical, experimental, ethnographic, conceptual, historical, socio-technical, policy-analytic, or critical-theoretical nature. JASIST also commissions in-depth review articles (“Advances in Information Science”) and reviews of print and other media.
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