scholarly journals Túl az impaktfaktoron. Gondolatok Stefanie Haustein könyve nyomán

2015 ◽  
Vol 156 (38) ◽  
pp. 1551-1552
Author(s):  
András Schubert
Keyword(s):  
Complex System ◽  
Impact Factor ◽  
User Groups ◽  
Journal Evaluation ◽  
Lay Reader ◽  
The Impact

The excellent book on multidimensional journal evaluation by Stefanie Haustein helps to find the place of the impact factor in the complex system of journal evaluation indicators. By delimiting the dimensions of evaluation and the user groups, the author of the book creates a framework that serves as a novel and useful guidance both for the lay reader and the expert. Orv. Hetil., 2015, 156(38), 1551–1552.

scholarly journals A multidimensional analysis of Aslib proceedings – using everything but the impact factor

2014 ◽  
Vol 66 (4) ◽  
pp. 358-380 ◽  
Author(s):  
Stefanie Haustein ◽  
Vincent Larivière
Keyword(s):  
Impact Factor ◽  
Citation Impact ◽  
Multidimensional Analysis ◽  
Scholarly Journals ◽  
Content Type ◽  
Five Dimensions ◽  
Publication History ◽  
History Of ◽  
Journal Evaluation ◽  
The Impact

Purpose – The purpose of this paper is to show that the journal impact factor (IF) is not able to reflect the full impact of scholarly journals and provides an overview of alternative and complementary methods in journal evaluation. Design/methodology/approach – Aslib Proceedings (AP) is exemplarily analyzed with a set of indicators from five dimensions of journal evaluation, i.e. journal output, content, perception and usage, citations and management to accurately reflect its various strengths and weaknesses beyond the IF. Findings – AP has become more international in terms of authors and more diverse regarding its topics. Citation impact is generally low and, with the exception of a special issue on blogs, remains world average. However, an evaluation of downloads and Mendeley readers reveals that the journal is an important source of information for professionals and students and certain topics are frequently read but not cited. Research limitations/implications – The study is limited to one journal. Practical implications – An overview of various indicators and methods is provided that can be applied in the quantitative evaluation of scholarly journals (and also to articles, authors and institutions). Originality/value – After a publication history of more than 60 years, this analysis takes stock of AP, highlighting strengths and weaknesses and developments over time. The case study provides an example and overview of the possibilities of multidimensional journal evaluation.

scholarly journals Analysis of Percentiles of Computer Science, Theory and Methods Journals CiteScore Versus Impact Factor

2020 ◽  
Vol 40 (01) ◽  
pp. 359-365
Author(s):  
Hilary I Okagbue ◽  
Shiela A. Bishop ◽  
Patience I. Adamu ◽  
Abiodun A. Opanuga ◽  
Emmanuela C.M. Obasi
Keyword(s):  
Impact Factor ◽  
Computer Science ◽  
Pearson Correlation ◽  
Journal Title ◽  
Science Theory ◽  
Median Test ◽  
Journal Evaluation ◽  
Level Of Significance ◽  
The Impact ◽  
The Relationship

Impact factor (Web of Science, Clarivate Analytics) and CiteScore (Scopus, Elsevier) are the two leading metrics for journal evaluation, assessment and ranking. The relationship between the two is now established, using their respective percentile in this paper for 105 journal in the Computer science, theory and methods (CSTM) subject category. The available studies did not consider the quartile comparison of the journal percentiles of the two database (Scopus and Science Citation Index expanded). The mean impact factor and CiteScore are 2.08 and 2.67 respectively. Pearson correlation coefficient between the impact factor and CiteScore is (0.919, p = 0.000) and between their respective journal percentiles is (r = 0.804, p = 0.000). Analysis of variance revealed that the means of the impact factor and CiteScore of the 105 CSTM journals are the same (F = 3.64, P = 0.058) but different (F = 38.94, P = 0.00) for their respective percentiles. The median test contradicts the ANOVA as the medians of impact factor and CiteScore are different at 0.05 level of significance. The median journal percentiles are the same for only 2 journal titles. The median journal percentile (SCIE) is greater than the median journal percentile (Scopus) for 5 journal titles and less than the median journal percentile (Scopus) for 98 journal titles. The same result was obtained when the percentiles were converted to quartiles, but in this case, the median journal quartiles are the same for 37 journal titles. The median journal quartile (SCIE) is greater than the median journal quartile (Scopus) for 67 journal titles and less than the median journal quartile (Scopus) in only one journal title. Only 37 (35 %) journals are in the same quartile of the two metrics. Caution is recommended in journal evaluation as conflicting different results can be obtained using the same metric.

The unknown acquaintance, or the impact factor and others

2007 ◽  
Vol 148 (4) ◽  
pp. 165-171
Author(s):  
Anna Berhidi ◽  
Edit Csajbók ◽  
Lívia Vasas
Keyword(s):  
Impact Factor ◽  
Citation Analysis ◽  
Index Number ◽  
Scientific Performance ◽  
H Index ◽  
Master List ◽  
The Many ◽  
The Impact

Nobody doubts the importance of the scientific performance’s evaluation. At the same time its way divides the group of experts. The present study mostly deals with the models of citation-analysis based evaluation. The aim of the authors is to present the background of the best known tool – Impact factor – since, according to the authors’ experience, to the many people use without knowing it well. In addition to the „nonofficial impact factor” and Euro-factor, the most promising index-number, h-index is presented. Finally new initiation – Index Copernicus Master List – is delineated, which is suitable to rank journals. Studying different indexes the authors make a proposal and complete the method of long standing for the evaluation of scientific performance.

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