Subjects: Library Science，Information Science >> Philology submitted time 2024-04-03 Cooperative journals: 《农业图书情报学报》
Abstract： Purpose/Significance The birth of the Internet has brought revolutionary impact on bibliometrics, giving rise to a number of online download indicators for academic literature. The most representative basic indicator among them is the download frequency, but it also includes the annual download rate, the total download volume, the download half-life, and the Google Scholar Index. The proposal of these indicators provides a new method and means of measuring scholarly dissemination and impact, which is a significant development of traditional bibliometrics and an important component of alternative metrics. Given the lack of indicators that comprehensively characterize the dissemination, impact, knowledge and information volume of academic journals, this paper proposes the download factor indicator to address this problem. Method/Process First, according to the changes of download frequency and citation frequency over the years, based on the citation data of CSSCI journals of library information and bibliology on CNKI, a panel data model was used to establish a prediction model of download frequency and citation frequency, and the optimal lag period for designing the download factor was determined. The indicator of download factor was proposed, that is, the average number of downloads per hundred times of each paper after 2 years of publication. This paper further used ridge regression to analyze the relationship between the download factor and the impact factor, h-index, and the number of articles. Results/Conclusions The download frequency with a lag of 1 year and 2 years determines 80% of the citation frequency. This article innovatively adopts a panel data model and comprehensively evaluates the impact of download frequency on citation frequency in both current and lagged periods, thereby greatly improving the prediction accuracy. The download factor can better measure the knowledge information volume, dissemination level, influence and academic quality of the journal. The timeline for downloading factor indicators is synchronized with the influencing factors, both within 2 years after the publication of journal articles, focusing on the evaluation of academic communication level. The download factor has the highest correlation with the main indicator of the impact of journal quality, the h-index, and has a high correlation with the impact factor and publication volume. It has good statistical indicator properties and is a comprehensive indicator for evaluating journals; the download factor index needs to be more inspection of application in disciplines and use of data. This article is based on the conclusions drawn from the research of 19 CSSCI journals in library and information science literature. The relationship between download frequency and citation frequency in other disciplines, as well as the construction of download factors, require further research in conjunction with the latest data.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-08-27 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] This paper aims to solve the problems that multiple attribute evaluation method of academic journals is numerous and evaluation result is inconsistent.[Method/process] This paper proposes a multi-attribute evaluation method based on cluster analysis method:the cluster results consistent degree of screening method. The principle is to cluster the original evaluation index at first. Then use feasible multi-attribute evaluation method to evaluate and the evaluation results are secondary clustering. Finally select the evaluation method according to the consistent degree of high low of evaluation results cluster and original index cluster results, and prefer to choose the evaluation method that the consistent degree of cluster results is highest. This paper selects 11 indexes based on the JCR2015 journal of mathematics, and uses the weighted linear summary, TOPSIS, VIKOR, principal component analysis and harmonic evaluation to evaluate respectively. Then the paper selects evaluation method based on the consistent degree of cluster results, and finds that the consistent degree of harmonic average is highest.[Result/conclusion] This method can be used to select Multiple attribute evaluation methods. The cluster type of setting has little influence on the result. This method has high robustness.
Subjects: Library Science，Information Science >> Information Science submitted time 2017-11-08 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】分析学术期刊来源指标与目标指标之间的关系以及由此导致的对期刊评价的影响。【方法】以 JCR 2015 年数学期刊为例, 采用典型相关分析对期刊来源指标与影响力指标的关系进行研究。【结果】实验结果表明: 特征因子是期刊影响力的主要指标; 期刊来源指标与影响力指标相关关系显著, 以特征因子为主的影响力指标 与载文量的相关系数高, 其次是引用半衰期, 后是文献选出率; 总被引频次、被引半衰期、影响因子、影响 因子百分位对特征因子的贡献较大, 而其他诸如他引影响因子、5年影响因子、即年指标的贡献较小; 影响力指 标比来源指标包含更多信息量。【局限】来源指标与影响力指标的关系尚需进一步检验。【结论】从期刊多属性 评价角度, 影响力指标的权重应大于来源指标的权重; 在影响力指标中, 有必要增加特征因子分值与标准特征 因子的权重, 并合理分配总被引频次、被引半衰期、影响因子、影响因子百分位的权重, 另一方面要适当降低他 引影响因子、5 年影响因子、即年指标的权重。
Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-31 Cooperative journals: 《农业图书情报学报》
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.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-08-27 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] This paper discusses the complementary problem between implicit indexes in science and technology evaluation. The complementary problem is that an index which does not increase or increases rarely can be compensated by other index increasing more, and the complementation is divided into equal complementation, excess complementation and under balance complementation. [Method/process] It designed a method of test and judgment, aiming at a certain nonlinear evaluation method, and maintaining an index constant, to calculate the change of evaluation value which is caused by increasing other different attribute index average, and compared with the change of linear weighted method evaluation value.[Result/conclusion] Research shows that the complementation between the index of multi-attribute evaluation method is a complex problem, which is influenced by various factors such as evaluation method, index data, weight arrangement and compensation value; the method of multi-attribute evaluation based on ratio is more likely to be the under balance complementation; due to the correlation between similar evaluation indexes, the indexes of complementary should be carried out between different attribute indexes; the complementation problem of indexes has a profound influence on the selection of multi-attribute evaluation methods, and in essence the index weight is changed euphemistically, which can be used as a method of evaluation test and management control.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-08-27 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] This paper analyzes the deep-level reasons for the abnormality in the index distinction degree and the bias of data distribution in the science and technology evaluation and believes that this is a deviation between the evaluation index value and the evaluation attribute essentially. That is, the evaluation index value can not reflect the essence of the evaluation attribute well.[Method/process] This paper proposes a new method to reduce the deviation between evaluation index value and evaluation attribute which is logarithmic median standardization, and takes JCR2016 mathematics journal for an example to conduct an empirical analysis.[Result/conclusion] The results show that citation indexs are more likely to show deviations between evaluation index value and evaluation attribute. The deviation between evaluation index value and evaluation attribute can be determined from multiple perspectives, such as index connotation analysis, pass rate, dispersion coefficient, median maximum ratio, concentration index HHI, etc. The use of logarithmic median standardization can greatly reduce the deviation of evaluation index value and evaluation attribute.
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