摘要
从文献的累积引文视角出发,以Logistic曲线为原型,拟合累积引文曲线模型,通过累积引文的曲线特征给出文献生命周期的三个阶段:沉睡期、苏醒期、衰老期。从沉睡强度和苏醒强度两个维度构建累积引文睡美人指数(cumulative citation sleeping beauty index,Cc index),提出了一种识别睡美人文献的无参数指标方法。对Web of Science平台在2008—2014年出版的超弦领域中的睡美人文献进行检验,结果表明Cc指数识别结果能很好地满足参数指标定义的睡美人文献,且对浅睡眠(假寐)文献、睡眠时间相对较短但苏醒强度大的睡美人文献具有较好的识别效果,同时能识别出全要素睡美人文献,更符合睡美人文献的本质特征。累积引文睡美人指数识别方法对其他研究领域的有效性有待进一步验证。
From the perspective of cumulative citation of literature,using the logistic curve as a prototype to fit the cumulative citation curve model,three stages of the life cycle of literature are given by the characteristics of the accumulated citation curve:the sleeping period,the waking period,and the aging period.From the two dimensions of sleep intensity and recovery intensity,we constructed a cumulative citation sleeping beauty index(Cc index),a non-parametric index method for identifying sleeping beauty literature.The sleeping beauty literature in the field of string theory published between 2008-2014 on the Web of Science(WoS)platform was tested.The results revealed that Cc index recognition results in more effectively satisfying the definition of the sleeping beauty document,and has a better recognition effect for the literature of light sleep(doze)and the literature of sleeping beauty with a relatively short sleep time but strong awakening intensity,and simultaneously,can better identify the all-elements-sleeping-beauties literatures,which is more in line with essential characteristics of the sleeping beauty literature.However,further verification is needed to determine if the cumulative citation sleep beauty index identification method is effective for other research fields.
作者
侯剑华
张雪雯
Hou Jianhua;Zhang Xuewen(School of Information Management,Sun Yat-sen University,Guangzhou 510006)
出处
《情报学报》
CSSCI
CSCD
北大核心
2020年第9期949-962,共14页
Journal of the China Society for Scientific and Technical Information
基金
国家社会科学基金一般项目“‘基于科学的创新’驱动新兴技术生成的机理及其促进政策研究”(17BGL031)。
关键词
科学睡美人
累积引文
累积引文睡美人指数
识别方法
scientific sleeping beauty
cumulative citation
cumulative citation sleeping beauty index
identification method
