scholarly journals Comparative Analysis Between Impact Factor and h-Index for Reproduction Biology Journals

2010 ◽  
Vol 9 (11) ◽  
pp. 1552-1555 ◽  
Author(s):  
Weidong Han ◽  
Qi Yu ◽  
Yanli Wang
2007 ◽  
Vol 148 (4) ◽  
pp. 165-171
Author(s):  
Anna Berhidi ◽  
Edit Csajbók ◽  
Lívia Vasas

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.


Author(s):  
Gianfranco Pacchioni

This chapter discusses how performance is measured in science, such as through the role of citation metrics. Next, the chapter discusses the pros and cons of bibliometric indexes, and of ‘impact factor’, which was introduced by Eugene Garfield in 1955 but not widely used until twenty years later. The various ways that journals attempt to improve their impact factors, and how this will affect science, are also examined. Besides impact factor, the role played by indicators in evaluating scientists, such as the recently introduced h-index, is explored. Finally, fashions and trends in science are touched upon, illustrated with personal anecdotes from the author.


2018 ◽  
Vol 35 (3) ◽  
pp. 7-9 ◽  
Author(s):  
Fayaz Ahmad Loan ◽  
Shueb Sheikh

Purpose This paper aims to identify the scholarly nature of the results retrieved by the Google Scholar on the five major global problems, i.e. global warming, economic recession, terrorism, HIV AIDS and child labour. Design/methodology/approach The five terms (global warming, economic recession, terrorism, HIV AIDS and child labour) were searched into the Google Scholar database, and the first 50 retrieved hits were manually analysed to record the relevant bibliographic details. The scholarship of the results was measured by quality indices like h-index, Altmetrics and Journal Impact Factor. The Scopus – the world’s biggest abstract and citation database – was used to identify the h-index of the prolific authors, citations of articles and impact factor of journals. Findings The study reveals that Google Scholar retrieves a good number of publications on the selected global problems from reputed publishers such as Nature Publishing Group, Elsevier, Cambridge University Press, Blackwell and Sage and published from well-developed countries such as the USA, UK and Switzerland. Google Scholar mostly retrieves articles and research papers from qualitative journals having a good impact factor such as Nature, Science, The Lancet, American Journal of Public Health, The Economic Journal, Social Science and Medicine and Annals of Tourism Research. These articles and books are contributed by the reputed authors having high h-index. The journal articles and books retrieved have also a good number of citations, although such results are limited. The results prove that Google Scholar is scholarly in nature to a great extent. Research limitations/implications The findings are limited to Google Scholar only and cannot be generalized for the rest of the search tools or databases. Further, the study included only five major global problems in the study, and thus, results cannot be applicable to other areas of knowledge. Practical implications The study is a checklist to know the retrieval performance of Google Scholar in terms of quality of content. Originality/value It is the first study of its kind that takes into account the nature of content on major global problems retrieved by the Google Scholar. It is also the first study that used bibliometric analysis to evaluate the quality of results retrieved.


2020 ◽  
pp. 104973152096377
Author(s):  
Monit Cheung ◽  
Patrick Leung

Purpose: With journal publishing being an important task for academicians, this article aims to help faculty and researchers increase their productivity by identifying journals with influential impacts on producing scientific knowledge. Method: Since 2004, the authors compiled and updated a journal list annually for social work faculty to use. This list aims to help faculty and researchers, including doctoral students, identify journals with significant scholarly impacts in social work and related fields for national and international recognition. Results: A total of 221 journals are included in the study, covering 44 social work journals with two indexes reported in the Journal Citation Reports® with Journal Impact Factor® and the h-index. Discussion: This list aims to help scholars find appropriate journals for article submissions. The criteria for the authors to select journals to be included in the publication list are also discussed.


2020 ◽  
Vol 146 (2) ◽  
pp. 247e-248e
Author(s):  
Matthew J. Davis ◽  
Amjed Abu-Ghname ◽  
Nikhil Agrawal ◽  
Edward M. Reece ◽  
Sebastian J. Winocour

Publications ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 42
Author(s):  
Salim Sazzed

The scientometric indices, such as the journal Impact Factor (IF) or SCImago Journal Rank (SJR), often play a determining role while choosing a journal for possible publication. The Editor-in-Chief (EiC), also known as a lead editor or chief editor, usually decides the outcomes (e.g., accept, reject) of the submitted manuscripts taking the reviewer’s feedback into account. This study investigates the associations between the EiC’s scholarly reputation (i.e., citation-level metrics) and the rankings of top Bioinformatics and Computational Biology (BCB) and Medical Informatics (MI) journals. I consider three scholarly indices (i.e., citation, h-index, and i-10 index) of the EiC and four scientometric indices (i.e., h5-index, h5-median, impact factor, and SJR) of various journals. To study the correlation between scientometric indices of the EiC and journal, I apply Spearman (ρ) and Kendall (τ) correlation coefficients. Moreover, I employ machine learning (ML) models for the journal’s SJR and IF predictions leveraging the EiC’s scholarly reputation indices. The analysis reveals no correlation between the EiC’s scholarly achievement and the journal’s quantitative metrics. ML models yield high prediction errors for SJR and IF estimations, which suggests that the EiC’s scholarly indices are not good representations of the journal rankings.


Sign in / Sign up

Export Citation Format

Share Document