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Journal of Library and Information Science in Agriculture ›› 2022, Vol. 34 ›› Issue (12): 55-64.doi: 10.13998/j.cnki.issn1002-1248.22-0374

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Key Indicators of Journal Evaluation Based on K-means and PLS-DA

YU Liping, PAN Weibo   

  1. School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018
  • Received:2022-05-23 Online:2022-12-05 Published:2023-03-15

Abstract: [Purpose/Significance] There are many evaluation indicators and methods for journal evaluation, and it is of great significance to study the importance of evaluation indicators of journals. This paper proposed an analysis framework for "post-event" analysis of the importance or weight of evaluation indicators. [Method/Process] This paper divides the journal evaluation indicators into "before" importance and "after" importance, and focuses on the "after" importance, that is, the determination of key indicators after objective cluster analysis. Taking the bibliometric indicators of JCR 2019 economics journals as the research object, K-means clustering was first used to obtain the classification of evaluation results, and then the key indicators of journal evaluation were calculated based on principal component analysis and partial least squares discriminant analysis, and the importance of each indicator was analyzed. Starting from the objective results and the meaning of the indicators themselves, this study expounded the reasons why indicators are important. [Results/Conclusions] Compared with the importance of "before", the importance of "after the fact" is to determine the evaluation results first, without involving weights, and completely based on data evaluation. There is relatively little controversy in the selection of methods. The indicator is more scientific and objective; the use of multi-factor evaluation can comprehensively reflect the common influence of each variable, and the use of the "dimension reduction" idea can better retain the information of the original variables and reduce the multicollinearity of the evaluation indicator; K-means cluster analysis methods, both the PLS-DA and PLS-DA models, are capable of evaluating and classifying journals. According to the results of PLS-DA, the VIP value of five indicators is greater than 1; the three most important indicators that affect the evaluation results of journals obtained by the PLS-DA method are the journal impact factor(IF), the other citation IF and the five-year IF, and the meaning of the indicators is the IF of other citations and the five-year IF make up for the shortcomings of the IF; the importance of the journal IF, the IF of other citations and the five-year IF is not much different, and the importance of the journal IF is relatively greater. In the quantitative evaluation of journals, it is necessary to use multi-index evaluation to make the evaluation more comprehensive and scientific; PLS-DA has a good effect on general journals, but the better journals have a general effect, and cannot effectively distinguish Class A journals.

Key words: journal evaluation, multi-attribute evaluation, indicator importance, K-means clustering, partial least squares discriminant analysis

CLC Number: 

  • G353.1
[1] 钟赛香, 胡鹏, 薛熙明, 等. 基于合理权重赋值方法选择的多因素综合评价模型——以JCR中70种人文地理期刊为例[J]. 地理学报, 2015, 70(12): 2011-2031.
ZHONG S X, HU P, XUE X M, et al.Multi-factor comprehensive evaluation model based on the selection of objective weight assignment method[J]. Acta geographica sinica, 2015, 70(12): 2011-2031.
[2] 俞立平. 客观赋权法本质及在科技评价中的应用研究——以学术期刊为例[J]. 情报理论与实践, 2021, 44(2): 50-56.
YU L P.Study on the essence of objective weighting method and its application in scientific and technological evaluation[J]. Information studies: Theory&application, 2021, 44(2): 50-56.
[3] 奉国和, 周榕鑫, 武佳佳. 基于熵权TOPSIS及因子分析的学术期刊综合评价研究[J]. 图书情报工作, 2018, 62(17): 84-95.
FENG G H, ZHOU R X, WU J J.Research on the comprehensive evaluation of academic journals based on entropy weight TOPSIS and factor analysis[J]. Library and information service, 2018, 62(17): 84-95.
[4] 熊国经, 熊玲玲, 陈小山. 基于PLS结构方程模型进行学术期刊评价的实证研究[J]. 情报理论与实践, 2017, 40(8): 117-121.
XIONG G J, XIONG L L, CHEN X S.An empirical study on the evaluation of academic journals based on PLS structural equation model[J]. Information studies: Theory&application, 2017, 40(8): 117-121.
[5] 李跃艳, 熊回香, 李晓敏. 基于主成分分析法的期刊评价模型构建[J]. 情报杂志, 2019, 38(7): 199-207.
LI Y Y, XIONG H X, LI X M.Construction of journal evaluation model based on the principal component analysis[J]. Journal of intelligence, 2019, 38(7): 199-207.
[6] 俞立平. 科技评价中关键指标的测度方法研究——以学术期刊评价为例[J]. 图书情报工作, 2017, 61(18): 93-97.
YU L P.The study on the measurement method of key indexes in the scientific and technological evaluation - Taking the evaluation of academic journals as an example[J]. Library and information service, 2017, 61(18): 93-97.
[7] 何学锋, 彭超群, 张曾荣. 科技期刊7项重要计量指标间的相互关系[J]. 编辑学报, 2003(6): 400-402.
HE X F, PENG C Q, ZHANG Z R.Relationships among seven important quantitative indicators of sci-tech journals[J]. Acta editologica, 2003(6): 400-402.
[8] 苏福, 柯平. 公共图书馆评估的关键指标探讨——以省级公共图书馆为例[J]. 图书馆建设, 2016(12): 15-20.
SU F, KE P.Research on key indicators of the public library assessment - Case study on provincial public libraries[J]. Library development, 2016(12): 15-20.
[9] RIC A, VINCENT L.History of the journal impact factor: Contingencies and consequences[J]. Scientometrics, 2009, 79(3): 24-31.
[10] 王新. 学科期刊的h-index、IF5和hTci-median实证评析[J]. 图书情报工作, 2014, 58(6): 105-112.
WANG X.Empirical research on subject journal assessment with h-index, IF5 and hTci-median[J]. Library and information service, 2014, 58(6): 105-112.
[11] ANTONIA A, RAúL G -J, JUAN C. Journals that increase their impact factor at least fourfold in a few years: The role of journal self-citations[J]. Scientometrics, 2009, 80(2): 26-32.
[12] 任胜利. 特征因子(Eigenfactor): 基于引证网络分析期刊和论文的重要性[J]. 中国科技期刊研究, 2009, 20(3): 415-418.
REN S L.Eigenfactor: The importance of journals and papers based on citation network analysis[J]. Chinese science and technology journal research, 2009, 20(3): 415-418.
[13] 赵星. JCR五年期影响因子探析[J]. 中国图书馆学报, 2010, 36(3): 120-126.
ZHAO X.An Analysis of the 5-year impact factor in JCR[J]. Journal of library science in China, 2010, 36(3): 120-126.
[14] BO L, IVAN C, LEO C, et al.Industrial PLS model variable selection using moving window variable importance in projection[J]. Chemometrics and intelligent laboratory systems, 2014, 135: 90-109.
[15] AFANADOR N L, TRAN T N, BLANCHET L, et al.Variable importance in PLS in the presence of autocorrelated data - Case studies in manufacturing processes[J]. Chemometrics and intelligent laboratory systems, 2014, 139: 56-76.
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