scholarly journals What are the variables associated with Altmetric scores?

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Amanda Costa Araujo ◽  
Adriane Aver Vanin ◽  
Dafne Port Nascimento ◽  
Gabrielle Zoldan Gonzalez ◽  
Leonardo Oliveira Pena Costa
Keyword(s):  
Systematic Review ◽  
Open Access ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Online Media ◽  
Press Releases ◽  
Citation Counts ◽  
The Impact ◽  
Journal Impact ◽  
Publishing Journal

Abstract Background Social media has been used to disseminate the contents of scientific articles. To measure the impact of this, a new tool called Altmetric was created. Altmetric aims to quantify the impact of each article through online media. This systematic review aims to describe the associations between the publishing journal and published article variables and Altmetric scores. Methods Searches on MEDLINE, EMBASE, CINAHL, CENTRAL, and Cochrane Library were conducted. We extracted data related to both the publishing article and the publishing journal associated with Altmetric scores. The methodological quality of included articles was analyzed by the Appraisal Tool for Cross-sectional Studies. Results A total of 19 articles were considered eligible. These articles summarized a total of 573,842 studies. Citation counts, journal impact factor, access counts, papers published as open access, and press releases generated by the publishing journal were associated with Altmetric scores. The magnitude of these associations ranged from weak to strong. Conclusion Citation counts and journal impact factor are the most common variables associated with Altmetric scores. Other variables such as access counts, papers published in open access journals, and the use of press releases are also likely to be associated with online media attention. Systematic review registration This review does not contain health-related outcomes. Therefore, it is not eligible for registration.

What are the variables associated with Altmetric scores? – An overview of methodological reviews (Preprint)

2019 ◽  
Author(s):  
Amanda Costa Araujo Sr ◽  
Adriane Aver Vanin Sr ◽  
Dafne Port Nascimento Sr ◽  
Gabrielle Zoldan Gonzalez Sr ◽  
Leonardo Oliveira Pena Costa Sr
Keyword(s):  
Open Access ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Cochrane Library ◽  
Open Access Journals ◽  
Citation Counts ◽  
Number Of Citations ◽  
The Impact ◽  
Journal Impact ◽  
Publishing Journal

BACKGROUND The most common way to assess the impact of an article is based upon the number of citations. However, the number of citations do not precisely reflect if the message of the paper is reaching a wider audience. Currently, social media has been used to disseminate contents of scientific articles. In order to measure this type of impact a new tool named Altmetric was created. Altmetric aims to quantify the impact of each article through the media online. OBJECTIVE This overview of methodological reviews aims to describe the associations between the publishing journal and the publishing articles variables with Altmetric scores. METHODS Search strategies on MEDLINE, EMBASE, CINAHL, CENTRAL and Cochrane Library including publications since the inception until July 2018 were conducted. We extracted data related to the publishing trial and the publishing journal associated with Altmetric scores. RESULTS A total of 11 studies were considered eligible. These studies summarized a total of 565,352 articles. The variables citation counts, journal impact factor, access counts (i.e. considered as the sum of HTML views and PDF downloads), papers published as open access and press release generated by the publishing journal were associated with Altmetric scores. The magnitudes of these correlations ranged from weak to moderate. CONCLUSIONS Citation counts and journal impact factor are the most common associators of high Altmetric scores. Other variables such as access counts, papers published in open access journals and the use of press releases are also likely to influence online media attention. CLINICALTRIAL N/A

scholarly journals What Are the Variables Associated With Altmetric Scores? – An Overview of Methodological Reviews

2020 ◽  
Author(s):  
Amanda Costa Araujo ◽  
Adriane Aver Vanin ◽  
Dafne Port Nascimento ◽  
Gabrielle Zoldan Gonzalez ◽  
Leonardo Oliveira Pena Costa
Keyword(s):  
Open Access ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Cochrane Library ◽  
Open Access Journals ◽  
The Media ◽  
Citation Counts ◽  
The Impact ◽  
Journal Impact ◽  
Publishing Journal

Abstract Background: Currently, social media has been used to disseminate contents of scientific articles. In order to measure this type of impact a new tool named Altmetric was created. Altmetric aims to quantify the impact of each article through the media online. This overview of methodological reviews aims to describe the associations between the publishing journal and the publishing articles variables with Altmetric scores. Methods: Search strategies on MEDLINE, EMBASE, CINAHL, CENTRAL and Cochrane Library. We extracted data related to the publishing trial and the publishing journal associated with Altmetric scores. Results: A total of 11 studies were considered eligible. These studies summarized a total of 565,352 articles. The variables citation counts, journal impact factor, access counts, papers published as open access and press release generated by the publishing journal were associated with Altmetric scores. The magnitudes of these correlations ranged from weak to moderate. Conclusion: Citation counts and journal impact factor are the most common associators of high Altmetric scores. Other variables such as access counts, papers published in open access journals and the use of press releases are also likely to influence online media attention.Systematic Review registrations: Not applicable

scholarly journals Modeling and Prediction of the Impact Factor of Journals Using Open-Access Databases

2020 ◽  
Vol 49 (5) ◽  
pp. 35-58
Author(s):  
Matthias Templ
Keyword(s):  
Open Access ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Web Of Science ◽  
Functional Relationships ◽  
Modeling And Prediction ◽  
Novel Approach ◽  
The Impact ◽  
Journal Impact ◽  
The Web

This article is motivated by the work as editor-in-chief of the Austrian Journal of Statistics and contains detailed analyses about the impact of the Austrian Journal of Statistics. The impact of a journal is typically expressed by journal metrics indicators. One of the important ones, the journal impact factor is calculated from the Web of Science (WoS) database by Clarivate Analytics. It is known that newly established journals or journals without membership in big publishers often face difficulties to be included, e.g., in the Science Citation Index (SCI) and thus they do not receive a WoS journal impact factor, as it is the case for example, for the Austrian Journal of Statistics. In this study, a novel approach is pursued modeling and predicting the WoS impact factor of journals using open access or partly open-access databases, like Google Scholar, ResearchGate, and Scopus. I hypothesize a functional linear dependency between citation counts in these databases and the journal impact factor. These functional relationships enable the development of a model that may allow estimating the impact factor for new, small, and independent journals not listed in SCI. However, only good results could be achieved with robust linear regression and well-chosen models. In addition, this study demonstrates that the WoS impact factor of SCI listed journals can be successfully estimated without using the Web of Science database and therefore the dependency of researchers and institutions to this popular database can be minimized. These results suggest that the statistical model developed here can be well applied to predict the WoS impact factor using alternative open-access databases. 

Analysis of the journal impact factor and related bibliometric indicators in education and educational research category

2021 ◽  
pp. 1-22
Author(s):  
Metin Orbay ◽  
Orhan Karamustafaoğlu ◽  
Ruben Miranda
Keyword(s):  
Impact Factor ◽  
Educational Research ◽  
Journal Impact Factor ◽  
Impact Factors ◽  
Bibliometric Indicators ◽  
Strongly Correlated ◽  
Starting Point ◽  
Consistent Assessment ◽  
The Impact ◽  
Journal Impact

This study analyzes the journal impact factor and related bibliometric indicators in Education and Educational Research (E&ER) category, highlighting the main differences among journal quartiles, using Web of Science (Social Sciences Citation Index, SSCI) as the data source. High impact journals (Q1) publish only slightly more papers than expected, which is different to other areas. The papers published in Q1 journal have greater average citations and lower uncitedness rates compared to other quartiles, although the differences among quartiles are lower than in other areas. The impact factor is only weakly negative correlated (r=-0.184) with the journal self-citation but strongly correlated with the citedness of the median journal paper (r= 0.864). Although this strong correlation exists, the impact factor is still far to be the perfect indicator for expected citations of a paper due to the high skewness of the citations distribution. This skewness was moderately correlated with the citations received by the most cited paper of the journal (r= 0.649) and the number of papers published by the journal (r= 0.484), but no important differences by journal quartiles were observed. In the period 2013–2018, the average journal impact factor in the E&ER has increased largely from 0.908 to 1.638, which is justified by the field growth but also by the increase in international collaboration and the share of papers published in open access. Despite their inherent limitations, the use of impact factors and related indicators is a starting point for introducing the use of bibliometric tools for objective and consistent assessment of researcher.

scholarly journals Comparison of the Impact Factors of the Most-Cited Cardiovascular Journals

2019 ◽  
Vol 124 (12) ◽  
pp. 1718-1724 ◽  
Author(s):  
Tobias Opthof
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
European Heart Journal ◽  
The Other ◽  
Impact Factors ◽  
Additional Advantage ◽  
The Right ◽  
Number Of Classes ◽  
The Impact ◽  
Journal Impact

In this article, I show that the distribution of citations to papers published by the top 30 journals in the category Cardiac & Cardiovascular Systems of the Web of Science is extremely skewed. This skewness is to the right, which means that there is a long tail of papers that are cited much more frequently than the other papers of the same journal. The consequence is that there is a large difference between the mean and the median of the citation of the papers published by the journals. I further found that there are no differences between the citation distributions of the top 4 journals European Heart Journal , Circulation , Journal of the American College of Cardiology , and Circulation Research . Despite the fact that the journal impact factor (IF) varied between 23.425 for Eur Heart J and 15.211 for Circ Res with the other 2 journals in between, the median citation of their articles plus reviews (IF Median) was 10 for all 4 journals. Given the fact that their citation distributions were similar, it is obvious that an indicator (IF Median) that reflects this similarity must be superior to the classical journal impact factor, which may indicate a nonexisting difference. It is underscored that the IF Median is substantially lower than the journal impact factor for all 30 journals under consideration in this article. Finally, the IF Median has the additional advantage that there is no artificial ranking of 128 journals in the category but rather an attribution of journals to a limited number of classes with comparable impact.

scholarly journals Ckj consolidation among Q1 Urology and Nephrology journals

2020 ◽  
Vol 13 (5) ◽  
pp. 723-727
Author(s):  
Alberto Ortiz
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Impact Factor ◽  
Cost Efficiency ◽  
Journal Impact Factor ◽  
Outcome Prediction ◽  
Web Of Science ◽  
Sglt2 Inhibitors ◽  
The Impact ◽  
Journal Impact

Abstract The Clinical Kidney Journal (ckj) impact factor from Clarivate’s Web of Science for 2019 was 3.388. This consolidates ckj among journals in the top 25% (first quartile, Q1) in the Urology and Nephrology field according to the journal impact factor. The manuscripts contributing the most to the impact factor focused on chronic kidney disease (CKD) epidemiology and evaluation, CKD complications and their management, cost-efficiency of renal replacement therapy, pathogenesis of CKD, familial kidney disease and the environment–genetics interface, onconephrology, technology, SGLT2 inhibitors and outcome prediction. We provide here an overview of the hottest and most impactful topics for 2017–19.

scholarly journals In praise of the impact factor

2020 ◽  
Author(s):  
John Antonakis ◽  
Nicolas Bastardoz ◽  
Philippe Jacquart
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Journal Articles ◽  
Good Proxy ◽  
Number Of Citations ◽  
The Impact ◽  
Journal Impact ◽  
Article Quality

The impact factor has been criticized on several fronts, including that the distribution of citations to journal articles is heavily skewed. We nuance these critiques and show that the number of citations an article receives is significantly predicted by journal impact factor. Thus, impact factor can be used as a reasonably good proxy of article quality.

scholarly journals Modeling and Simulation Analysis of Journal Impact Factor Dynamics Based on Submission and Citation Rules

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Jian Zhou ◽  
Lin Feng ◽  
Ning Cai ◽  
Jie Yang
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Simulation Analysis ◽  
Impact Factors ◽  
Model Parameters ◽  
Review Time ◽  
Citation Window ◽  
Sociological Factors ◽  
The Impact ◽  
Journal Impact

The variation of the journal impact factor is affected by many statistical and sociological factors such as the size of citation window and subject difference. In this work, we develop an impact factor dynamics model based on the parallel system, which can be used to analyze the correlation between the impact factor and certain elements. The parallel model aims to simulate the submission and citation behaviors of the papers in journals belonging to a similar subject, in a distributed manner. We perform Monte Carlo simulations to show how the model parameters influence the impact factor dynamics. Through extensive simulations, we reveal the important role that certain statistics elements and behaviors play to affect impact factors. The experimental results and analysis on actual data demonstrate that the value of the JIF is comprehensively influenced by the average review time, average number of references, and aging distribution of citation.

The Critical Care Medicine Research: A Systematic Review

2020 ◽  
Author(s):  
Kawthar Hasan Jasim
Keyword(s):  
Systematic Review ◽  
Critical Care ◽  
Cost Effectiveness ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Journal Citation Report ◽  
Critical Care Medicine ◽  
Medicine Research ◽  
The Cost ◽  
Journal Impact

Objectives: The cost-effectiveness terminology is a common term used in the critical care medicine research. A systematic review analysis was conducted to study the patterns of the use and misuse of the cost-effectiveness terminology in the critical care medicine literature between 1998 and 2018. Methods: A search in the inCite journal citation report was done to identify all the critical care medicine journals. An independednt search done to identify all the articles between 1980 to 2018 that claimed in their abstracts/article to perform a cost-effectiveness analysis (CEA). Eligible articles were included and analyzed using x2-test. The articles were categorized into four different levels based on the appropriateness of CEA terminology use. The analysis performed to assess the association between the appropriateness of CEA terminology and the journal impact factor (IF), author background, and the publication year (5-year time points). Results: Out of 7,835 articles in targeted subject category, 76 met the inclusion criteria, but 50 of them were analyzed. Of these 50 articles, 32 (64.0%) met the appropriate criterion of CEA terminology use. 71.4% of articles published in journals with IF: 3.0 - 21.4 were appropriately using CEA term compared to 54.5% studies that are published in journals with IF: 0.4 - 2.8. Of these articles, which are appropriately use CEA terminology, 56.2% of the articles have at least one author with health economics expertise. Conclusion and recommendation: The preliminary data suggest that there is an association between the level of appropriateness and journal impact factor and the author health-economic background authorship. However, we did not demonstrate changes in the level of appropriateness with time. Decision-makers, authors, and editors should pay better attention in seeking ways to monitor the appropriate use of “cost-effectiveness” terminology. More future studies should be done in this context.

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