Journal-level Metrics can be useful when considering the impact of the journal an article appears in. Journal-level Metrics focus on citation rate, which is calculated by contrasting the number of citations a journal receives in a year compared to the number of articles they publish. A higher proportion of citations to publications may indicate higher quality: but not necessarily.
The impact of a particular journal (you may hear of this referred to as 'Tier One' or 'Top Tier' journals) will vary between disciplines, and should be used with a critical eye. This page will highlight several of the journal-ranking tools that are available, but remember, journal-level metrics should not be used to measure impact or influence of authors, institutions, or articles. As always you should take these results as a guide but remember that they can be manipulated.
Other considerations:
Review journals often have higher journal impact factors.
You can’t compare journals from different categories.
Different resources have different subject focuses: for example, Web of Science only calculates journal metrics for the science, engineering and social science journals indexed in their database, which does not mean the absence of a journal equates to low impact.
For more information on these metrics, use the tabs to navigate.
Journal Citation Reports, or JCR, is an annual publication released by Clarivate and based on the Web of Science collection. This resource incorporates Journal Impact Factor (JIF) and Eigenfactor to highlight the strength of a particular journal in its impact factor over the past year. JCR is a useful resource for researchers hoping to publish in a high impact journal.
Journal Citation Reports is sourced from Web of Science Core Collection, the premier citation index on the Web of Science platform. Journals must undergo a rigorous evaluation by our editorial team in order to be covered in Web of Science Core Collection. We capture the cited references for all content from these journals, and we link those cited references to the cited papers. This article-level citation data is aggregated to the journal-level at the end of the year to create the indicators available in JCR. Over 11,500 titles from the Science Citation Index-Expanded and Social Sciences Citation Index are covered in JCR. The Science and Social Science editions of JCR are released annually. Source
To access Journal Citation Reports, click below.
The Journal Impact Factor (JIF) is a number that is calculated by dividing the number of citations received in the current year by the number of papers published in the journal in the previous two calendar years. This concept was first proposed in 1927 by Gross and Gross and developed in 1955 by Garfield, with the idea of identifying the most relevant journals in an area of study. This formula, which emerged as a way of removing bias to rank journals in a subjective way, has undergone significant changes over the last century, but remains a popular metric.
How is Journal Impact Factor calculated?
This metric divides the number of citations from one year by the number of articles published over the past two years. For example:
The (fictional) journal TMU Library Times (TMULT) published 22 eligible (i.e citable) articles in 2021 and 19 eligible articles in 2022. In 2023, these articles received 245 citations from other publications.
To calculate the JIF for 2023, you would divide the 245 citations by the 41 publications over the previous two years, which equals 5.97. Thus, we can state that TMULT's JIF for 2023 is 5.97, as the articles published were cited on average 5.97 times.
Areas of caution for Journal Impact Factor
Journal Impact Factors may be manipulated, through a number of strategies:
Works Cited
Garfield E. The history and meaning of the journal impact factor. JAMA. 2006;295(1):90–3. 10.1001/jama.295.1.90
Gross PL, Gross EM. College Libraries and Chemical Education. Science. 1927;66(1713):385–9. 10.1126/science.66.1713.385.
Eigenfactor is a journal-level metric developed in 2008 by Jevin West and Carl Bergstrom, that determines the total importance of a scientific journal in relation to a much broader network of connections.
Features of Eigenfactor include:
To search Eigenfactor scores, visit the link listed below.
Works cited
Bergstrom, C. T.; West, J. D.; Wiseman, M. A. (2008). "The Eigenfactor Metrics". Journal of Neuroscience. 28 (45): 11433–11434. doi:10.1523/JNEUROSCI.0003-08.2008.
Google Scholar Metrics are a user-friendly approach to journal rankings, and collates citation data to allow researchers quick and easy access to how their research is performing in the field.
In addition to personal metrics, researchers can arrange searches by journal title, which includes the h5-index and h5-median scores. The h5-index summarises the h-index for articles published in the last 5 complete years, while the h5-median for a publication is the median number of citations for the articles that make up its h5-index.
You can sort the results on the page by the top 100 publications under each category, and filter by subcategory and language to discover the journal that is best for your publication.
The SCImago (from SCientific Influence and pronounced sigh-mago) Journal Rank (SJR) is a journal ranking based on Scopus data, that is calculated by dividing the number of citations received by the journal in the given year from primary items (articles, reviews and conference papers) to primary items published in the three previous years by the number of primary items published in the journal in the three previous years.
Benefits to this ranking include:
To explore SCImago, click the link below.
This guide has been created by the Toronto Metropolitan University Library and is licensed under a Creative Commons Attribution International 4.0 License unless otherwise marked.