情报研究

基于引用内容的论文影响力研究——以诺贝尔奖获得者论文为例

  • 刘盛博 ,
  • 王博 ,
  • 唐德龙 ,
  • 马翔 ,
  • 丁堃
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  • 1. 大连理工大学高等教育研究院 大连 116023;
    2. 大连工业大学管理学院 大连 116034;
    3. 大连理工大学WISE实验室 大连 116023
刘盛博(ORCID:0000-0002-0163-1213),讲师,E-mail:liushengbo1121@gmail.com;王博(ORCID:0000-0001-8289-6688),讲师;唐德龙(ORCID:0000-0003-2667-0988),博士研究生;马翔(ORCID:0000-0002-0956-9952),硕士研究生;丁堃(ORCID:0000-0001-5280-9504),教授,博士生导师。

收稿日期: 2015-10-03

  修回日期: 2015-12-02

  网络出版日期: 2015-12-20

基金资助

本文系国家自然科学基金项目"基于引用内容的单篇论文质量评价体系研究"(项目编号:71503030)和中国博士后科学基金项目"基于全文信息的科技论文引用内容评价研究"(项目编号:2015M571312)研究成果之一。

Research on Paper Influence Based on Citation Context: A Case Study of the Nobel Prize Winner's Paper

  • Liu Shengbo ,
  • Wang Bo ,
  • Tang Delong ,
  • Ma Xiang ,
  • Ding Kun
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  • 1. Institute of Higher Education, Dalian University of Technology, Dalian 116023;
    2. School of Management, Dalian Polytechnic University, Dalian, 116034;
    3. WISE Lab, Dalian University of Technology, Dalian 116023

Received date: 2015-10-03

  Revised date: 2015-12-02

  Online published: 2015-12-20

摘要

[目的/意义]论文被引频次只能反映论文的宏观影响力,无法揭示论文在他人研究中的具体作用和影响,因此,本文提出从引用内容的主题和功能两方面对论文的影响力进行分析。[方法/过程]以2014年诺贝尔生理学或医学奖获得者J.O'Keefe的高被引论文为实例,首先,采用文献计量学方法对引用内容主题进行分析;对其,影响范围及领域进行可视化分析;其次,从引用性质和功能角度,将引用内容分成正面引用、负面引用和中性引用;最后,将中性引用进一步划分为3类,分别是研究背景介绍、理论基础和实验基础。[结果/结论]结果表明,共词分析可以很好地表达论文影响的主题领域;引用内容的分类可以提供一篇论文被引用的多方面原因。在本实验中没有负面引用,多于10%的引用为正面引用,大约50%的中性引用都是作者在研究背景章节中介绍与施引文献相关的研究工作。

本文引用格式

刘盛博 , 王博 , 唐德龙 , 马翔 , 丁堃 . 基于引用内容的论文影响力研究——以诺贝尔奖获得者论文为例[J]. 图书情报工作, 2015 , 59(24) : 109 -114 . DOI: 10.13266/j.issn.0252-3116.2015.24.016

Abstract

[Purpose/significance] The citation frequency of a paper can only reflect its macro influence. It cannot reveal the specific role and impact of the cited paper in others' studies. Paper influence is analyzed from two aspects of the themes and the functions of the citation context.[Method/process] The citation contexts of a highly cited paper of O'Keefe, who won the 2014 Nobel Prize in physiology/medicine prize winners, are extracted as the experiment data set. First, the themes of citation context are analyzed with bibliometrics methods, and the influence fields are visualized. Second, the citation context is classified into three categories as positive, negative and neutral. And the neutral citations are also classified into three sub categories, related work in research background or introduction, theoretical foundation, and experimental foundation.[Result/conclusion] The results show that the co-occurrence method is very useful for describing the themes of citation contexts, and the classification of citation contexts can provide more information about how and why a paper is highly cited. There is no negative citation in this experiment, more than 10% citation contexts are positive citation, and about 50% of neutral ciations are related to background or introduction.

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