摘要
[目的/意义]从不同学科领域识别出"睡美人"论文并在科学界中广泛传播与使用,能够极大程度实现此类科技成果的科学价值,促进科学领域的发展与进步。[方法/过程]综合运用K值算法、三指标法和文献被引延迟指数,从神经科学领域1990-2010年发表的905 418篇论文中识别出"睡美人"论文,并对"睡美人"论文的期刊分布、论文篇幅、作者数量和睡眠特征等影响因素进行计量分析。[结果/结论]实证结果显示:(1)融合K值算法与三指标法能够从神经科学领域90余万篇论文中识别出26篇"睡美人"论文,识别准确率较高;(2)文献被引延迟指数方法识别出的"睡美人"论文数量较多,达到65篇,识别准确率略低,然而该方法的计算效率较高;(3)两类方法识别出的26篇共同"睡美人"论文的睡眠深度范围为0.11~1.63次,睡眠时长相对较短,平均时长为9.88年。此外,除总被引频次外,神经科学领域"睡美人"论文形成的影响因素与期刊影响因子、论文作者数量和篇幅等特征均不显著相关。
[Purpose/Significance] The identification of Sleeping Beauties from different disciplines and their wide dissemination and utilization in the scientific community can greatly come true the scientific value of such scientific achievements and promote the development and progress of scientific fields. [Methodology/process] By using k-value algorithm,three-indicator recognition method and citation delay index,the Sleeping Beauties were identified from 905418 articles published in Neuroscience from 1990 to 2010 were analyzed,as sell as influencing factors of these Sleeping Beauties as journal distribution,paper length,number of authors. [Result/Conclusion] The empirical results showed that:(1)26 Sleeping Beauties were identified via the combination of K-value algorithm and three-index method from more than 900000 articles in the field of Neuroscience,with high recognition accuracy.(2)A large number of Sleeping Beauties were identified via the citation delay index,up to 65,with slightly lower recognition accuracy,but the method had higher computational efficiency.(3)The sleeping depth of the 26 same Sleeping Beauties identified by two types of methods from Neuroscience ranged from0. 11 to 1. 63 times,and the sleeping duration was relatively short,with an average of 9. 88 years. In addition,the influencing factors of the formation of Sleeping Beauties in Neuroscience were not significantly correlated with the impact factor,the number of authors and length of papers,except the total citation frequency.
作者
胡泽文
任萍
沈佳慧
Hu Zewen;Ren Ping;Shen Jiahui(School of Management Science and Engineering,Nanjing University of Information Science&Technology,Nanjing 210044,China)
出处
《现代情报》
CSSCI
2022年第3期147-156,共10页
Journal of Modern Information
基金
国家社会科学基金项目“面向海量科技文献的潜在‘精品’识别方法与应用研究”(项目编号:20CTQ031)
江苏省社会科学基金项目“社会科学领域文献价值分层与识别机制研究”(项目编号:19TQC004)。
关键词
“睡美人”论文
神经科学
K值算法
三指标法
被引延迟指数
计量特征
影响因素
Key wods:Sleeping Beauties
neuroscience
K-value algorithm
three index method
cited delay index
bibliometric characteristics
influencing factors