科研人员职业生涯学术论文相似度及其对被引频次的影响分析  

Impact of Article Similarity on Citation Counts during Researchers’ Career Development

作　　者：张丽华 张康宁 赵迎光 张志强[3,4] Zhang Lihua;Zhang Kangning;Zhao Yingguang;Zhang Zhiqiang(School of Information,Shanxi University of Finance and Economics,Taiyuan 030006;Beijing Jiaotong University Library,Beijing 100044;Chengdu Library and Information Center,Chinese Academy of Sciences,Chengdu 610041;Department of Library,Information and Archives Management,School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190)

机构地区：[1]山西财经大学信息学院,太原030006 [2]北京交通大学图书馆,北京100044 [3]中国科学院成都文献情报中心,成都610041 [4]中国科学院大学经济与管理学院图书情报与档案管理系,北京100190

出　　处：《情报学报》2022年第8期822-831,共10页Journal of the China Society for Scientific and Technical Information

基　　金：中国博士后科学基金资助项目“研究评估中科学计量学的不确定性现象及应对策略研究”(2018M631551);山西省软科学研究计划项目“山西省科技人才评价工作中量化指标的滥用及应对策略研究”(2018041045-1)。

摘　　要：在科研人员的职业生涯中,是否应该适时转移研究主题是每个科研人员都非常关注的问题。本文旨在探讨科研人员职业生涯学术论文相似度及其对被引频次的影响。基于“商业与经济”和“计算机科学与人工智能”两个学科的作者与论文数据,以学术论文相似度为自变量,论文被引频次为因变量,作者数、论文篇幅、参考文献数、期刊影响因子以及作者学术年龄为控制变量,构建负二项回归模型。结果表明,两个学科科研人员职业生涯学术论文相似度呈现“中间高、两边低”的分布特征,商业与经济学科39.5%的科研人员研究主题发生转移,学术论文相似度不会影响其被引频次,而计算机科学与人工智能学科45.6%的科研人员研究主题发生转移,学术论文相似度对其被引频次存在影响。During each researcher’ s career development, it is fundamental that they pay attention to the serious issue of identifying an appropriate time to change their research direction, if needed. This study aims to explore the impact of article similarity on citation counts during researchers’ career development. Based on the data of authors and papers of“Business & Economics”and“Computer Science, Artificial Intelligence,”a negative binomial regression model was constructed with article similarity as the independent variable;citation counts of article as the dependent variable;and the number of authors, length of papers, number of references, journal influence factors, and author’s academic age as control variables.The results show that article similarity during a researcher’s career development in the two disciplines presents the distribution characteristic of“high in the middle and low on both sides.”Notably, 39.5 percent of researchers in Business & Economics switched their research topics, and article similarity proved to have no effect on citation counts. However, 45.6 percent of researchers in Computer Science, Artificial Intelligence also changed their research topics, and article similarity impacted citation counts.

关 键 词：论文相似度 被引频次 科研人员 研究主题转移 

分 类 号：G353.1[文化科学—情报学]