Academic Journal Ranking Metrics: Impact Factor, Eigenfactor, H-Index, and More

Academic journal ranking metrics

Academic journal ranking metrics measure the influence and impact of journals, individual articles, and researchers. Different metrics capture different things, and understanding what each one measures matters when you're choosing where to submit, evaluating someone else's work, or building your own academic record. This guide explains the most widely used metrics, how each is calculated, what each is good for, and the limitations of each. For the practical workflow of finding rankings and using them when choosing a target journal, see the companion article on how to find and use academic journal rankings.


Quick Answer: What Each Metric Measures

Impact Factor.
Average citations per article in a journal over two years. The most widely used journal metric.

Eigenfactor.
Total citation impact of a journal, weighted by the prestige of the citing journals. Influenced by journal size.

Article Influence Score.
Per-article version of eigenfactor. Above 1 = above-average impact.

H-Index.
Researcher metric. An h-index of n means n papers each cited n times. Balances output and impact.

G-Index.
Researcher metric that gives more weight to highly-cited papers than the h-index does.

i10-Index.
Number of an author's papers cited at least 10 times. Google Scholar only.

SJR (Scimago Journal Rank).
Prestige-weighted journal score from Scopus data. Provides Q1, Q2, Q3, Q4 quartile rankings.

CiteScore.
Elsevier's journal metric. Like impact factor but uses a four-year citation window.

SNIP.
Citation impact normalized by the citation patterns in a journal's field. Useful for cross-field comparison.

h5-Index.
Google Scholar's journal ranking based on h-index over the previous five years.


Journal Ranking Metrics at a Glance

Metric What It Measures Time Window Source Cross-Field Compare?
Impact Factor (JIF) Average citations per article 2 years Clarivate (JCR) No
Eigenfactor Prestige-weighted total citations 5 years Eigenfactor.org Limited
Article Influence Score Per-article eigenfactor 5 years Eigenfactor.org Limited
SJR Prestige-weighted citation score 3 years Scimago (free) Yes (via quartiles)
CiteScore Average citations per article 4 years Scopus No
SNIP Field-normalized citation impact 3 years Scopus Yes
h5-Index Journal h-index over 5 years 5 years Google Scholar Limited

Researcher Metrics at a Glance

Metric What It Measures Calculated How Where to Find
H-Index Output and impact combined n papers each cited n times Google Scholar, Web of Science, Scopus
G-Index Output weighted toward top papers Top g papers cited at least g² times Some Scopus tools; less common
i10-Index Output above a citation threshold Number of papers cited 10+ times Google Scholar only
m-Index Career-stage-adjusted h-index h-index divided by years since first publication Calculated manually

Journal Ranking Metrics Explained

Impact Factor (JIF)

The impact factor is one of the most widely used metrics for ranking academic journals. It measures the average number of citations received per article published in a journal over the previous two-year period. Impact factor is published annually by Clarivate in the Journal Citation Reports.


A journal with a higher impact factor is generally considered more prestigious within its subject category. Impact factors should not be compared across different fields, however, because citation practices vary enormously by discipline. A high-impact journal in mathematics will have a far lower impact factor than a high-impact journal in molecular biology.


One commonly cited criticism of the impact factor is that journals publishing review articles tend to score higher than journals publishing primarily original research, since reviews are typically cited more frequently. Despite these limitations, the impact factor remains the single most cited metric in academic hiring, promotion, and grant decisions.


Eigenfactor

The eigenfactor is calculated based on the total number of citations from articles published within a journal, weighted by the prestige of the citing journals. The concept is similar to Google's PageRank algorithm. Citations from highly-regarded journals count more than citations from lesser-regarded ones.


Eigenfactor is influenced by journal size. Larger journals that publish more articles generally have higher eigenfactor scores than smaller journals, even when the smaller journals are highly cited per article. The journal Nature, for example, consistently maintains a high eigenfactor score in part because of its large publication volume.


Article Influence Score

The article influence score measures the average impact of a single article within a journal. It is calculated by dividing the eigenfactor by the total number of articles published in the journal over the same period. Scores above 1 indicate above-average impact. Scores below 1 suggest lower relative impact. Article influence score is the per-article version of eigenfactor and makes journal-to-journal comparison easier.


SJR (Scimago Journal Rank)

The SJR is a prestige-weighted journal metric calculated from Scopus citation data. Like eigenfactor, it weights citations from prestigious journals more heavily than citations from less prestigious ones. SJR also categorizes journals into quartiles (Q1, Q2, Q3, Q4) within their subject categories, which makes relative standing easier to interpret than raw scores.


SJR is freely available at scimagojr.com without a library subscription, covers a broader range of journals than the Journal Citation Reports, and is increasingly accepted by research funding bodies as evidence of publication quality.


CiteScore

CiteScore is Elsevier's journal ranking metric, also based on Scopus data. Unlike impact factor, which uses a two-year citation window, CiteScore uses a four-year window. The longer window gives CiteScore more stability and makes it more useful for fields where research takes longer to accumulate citations. CiteScore is freely accessible through Scopus Sources and is increasingly used alongside impact factor as a complementary measure.


SNIP (Source Normalized Impact per Paper)

SNIP adjusts citation counts based on the average number of citations in a field. This makes SNIP more suitable than impact factor for comparing journals across different disciplines, because it corrects for the fact that citation practices vary enormously between fields. A SNIP score above 1.0 indicates above-average citation impact relative to the field. SNIP is calculated from Scopus data and accessible through Scopus.


h5-Index

The h5-index is Google Scholar's journal ranking metric. It measures the h-index of a journal calculated over the previous five years rather than across the journal's full history. Google Scholar publishes h5-index rankings of top journals by subject area, freely available at scholar.google.com/citations. The h5-index is particularly useful for fields underrepresented in Scopus and Web of Science.


Researcher Metrics Explained

H-Index

The h-index measures both the output and impact of an individual researcher. A researcher has an h-index of n if they have published at least n papers that have each been cited at least n times. A researcher with an h-index of 10 has published at least 10 papers that have each been cited at least 10 times. A researcher with an h-index of 25 has published at least 25 papers cited at least 25 times each.


The h-index attempts to balance research output (the number of papers published) against research impact (the number of citations received). It is the most widely cited researcher-level metric in academic hiring, promotion, and tenure decisions.


Limitations of the h-index include that it favors researchers with long publication records over early-career researchers, it varies enormously by field (h-indexes in the life sciences are typically higher than in mathematics or the humanities), and it can be inflated by self-citation. The h-index is calculated automatically by Google Scholar, Web of Science, and Scopus, although the value reported by each platform varies based on which publications are indexed.


G-Index

The g-index was developed in 2006 to give greater weight to highly cited publications than the h-index does. While the h-index counts the number of papers with at least n citations, the g-index considers the cumulative citation count of the top g papers, with the requirement that those g papers together have received at least g² citations.


This means the g-index is more sensitive to a researcher's most influential work, while the h-index is more sensitive to consistent productivity. A researcher with a small number of highly cited papers will typically have a g-index notably higher than their h-index. The g-index is not yet as widely used as the h-index, partly because the major databases display h-index more prominently, but it provides a useful complement when evaluating researchers whose impact is concentrated in a few highly influential publications rather than spread across many papers.


i10-Index

The i10-index is a simpler metric used exclusively by Google Scholar. It counts the number of publications an author has that have received more than 10 citations. The i10-index is easy to calculate and freely available, but its main limitation is that it is only measured by one platform, and it captures less nuance than the h-index or g-index. The i10-index is most useful as a quick supplementary measure, not as a primary indicator of research impact.


m-Index

The m-index is the h-index divided by the number of years since the researcher's first publication. The m-index adjusts for career stage, which makes it useful for comparing early-career researchers to senior researchers. An m-index above 1 typically signals strong research impact relative to career length. The m-index is calculated manually rather than reported automatically by databases.


Limitations of Quantitative Metrics

All citation-based metrics have known limitations, and several have been the subject of formal critique within the academic community. Researchers should treat these metrics as useful but imperfect tools.


  • Field differences.
    Citation practices vary enormously between disciplines. A journal with an impact factor of 3 in mathematics is not comparable to a journal with an impact factor of 3 in molecular biology. Always compare metrics within the same subject category.
  • Productivity correlation.
    Publication volume is highly correlated with h-index values, which means the metric may reflect productivity more than research quality.
  • Oversimplification.
    Mathematicians and other researchers have argued that reducing a researcher's career to a single numerical value is an oversimplification of academic quality.
  • Review article bias.
    Journals publishing review articles score higher on impact factor than journals publishing primarily original research, because reviews are cited more frequently.
  • Self-citation and gaming.
    Some metrics can be inflated by self-citation or by editorial practices designed to boost scores. Always interpret metrics in context.
  • Database differences.
    H-index values differ between Google Scholar, Web of Science, and Scopus because each database indexes a different set of publications. The same researcher will have different h-index values on different platforms.

Where to Find These Metrics

Each metric is published by a different platform. Here is the briefest possible reference. For a step-by-step workflow on accessing these tools, choosing a target journal, and using rankings strategically, see the companion article on how to find and use academic journal rankings.



Frequently Asked Questions

What is the impact factor of an academic journal?

The impact factor is one of the most widely used metrics for ranking academic journals. It measures the average number of citations received per article published in a journal over a two-year period and is published annually by Clarivate in the Journal Citation Reports. A journal with a higher impact factor is generally considered more prestigious within its subject category, although impact factors should not be compared across different fields because citation practices vary enormously by discipline. One commonly cited criticism of the impact factor is that journals publishing review articles tend to score higher than journals publishing primarily original research, since reviews are typically cited more frequently. Despite these limitations, the impact factor remains the single most cited metric in academic hiring, promotion, and grant decisions.


What is the difference between impact factor and eigenfactor?

Impact factor and eigenfactor are related but distinct measures of journal influence. Impact factor measures the average number of citations per article over a two-year period and is independent of journal size. Eigenfactor measures the total citation impact of a journal, accounting for both the number of citations and the prestige of the citing journals, similar in concept to Google's PageRank algorithm. Eigenfactor is influenced by journal size. Larger journals that publish more articles generally have higher eigenfactor scores than smaller journals, even when the smaller journals are highly cited per article. The article influence score is derived from the eigenfactor by dividing it by the total number of articles published in the journal, producing a per-article measure that is more comparable across journals of different sizes.


What is the h-index and how is it calculated?

The h-index is a metric for measuring the productivity and impact of an individual researcher's published work. A researcher has an h-index of n if they have published at least n papers that have each been cited at least n times. A researcher with an h-index of 10 has published at least 10 papers that have each been cited at least 10 times. The h-index attempts to balance research output (the number of papers published) against research impact (the number of citations received). Limitations include that it favors researchers with long publication records over early-career researchers, it varies enormously by field, and it can be inflated by self-citation. The h-index is calculated automatically by Google Scholar, Web of Science, and Scopus, although the value reported by each platform varies based on which publications are indexed.


How is the g-index different from the h-index?

The g-index, developed in 2006, gives greater weight to highly cited publications than the h-index does. While the h-index counts the number of papers with at least n citations, the g-index considers the cumulative citation count of the top g papers, with the requirement that those g papers together have received at least g² citations. This means the g-index is more sensitive to a researcher's most influential work, while the h-index is more sensitive to consistent productivity. A researcher with a small number of highly cited papers will typically have a g-index notably higher than their h-index.


What is the i10-index?

The i10-index is a researcher metric used exclusively by Google Scholar. It counts the number of publications an author has that have received at least 10 citations. The i10-index is easy to calculate and freely available, but its main limitation is that it is only measured by one platform, and it captures less nuance than the h-index or g-index. The i10-index is most useful as a quick supplementary measure rather than a primary indicator of research impact.


What is the article influence score?

The article influence score measures the average impact of a single article within a journal. It is calculated by dividing the eigenfactor by the total number of articles published in the journal over the same period. Scores above 1 indicate above-average impact. Scores below 1 suggest lower relative impact. Article influence score is the per-article version of eigenfactor and makes journal-to-journal comparison easier than raw eigenfactor scores, which are influenced by journal size.


What is SJR and how is it different from impact factor?

SJR (Scimago Journal Rank) is a prestige-weighted journal metric calculated from Scopus citation data. Unlike impact factor, which counts all citations equally, SJR weights citations from prestigious journals more heavily than citations from less prestigious ones, similar in concept to Google's PageRank algorithm. SJR also categorizes journals into quartiles (Q1, Q2, Q3, Q4) within their subject categories, making relative standing easier to interpret than raw impact factor numbers. SJR is freely available at scimagojr.com without a library subscription and covers a broader range of journals than the Journal Citation Reports.


What is CiteScore?

CiteScore is Elsevier's journal ranking metric, calculated from Scopus citation data. Like impact factor, CiteScore measures average citations per article. The key difference is the time window: CiteScore uses a four-year citation window where impact factor uses two years. The longer window gives CiteScore more stability and makes it more useful for fields where research takes longer to accumulate citations. CiteScore is freely accessible through Scopus Sources.


What is SNIP and when should I use it?

SNIP (Source Normalized Impact per Paper) adjusts citation counts based on the average number of citations in a field, making it suitable for comparing journals across different disciplines. A SNIP score above 1.0 indicates above-average citation impact relative to the field. SNIP is most useful when you need to compare journals across fields where citation practices differ significantly, such as comparing a mathematics journal to a biology journal. SNIP is calculated from Scopus data and accessible through Scopus.


Which metric is the most accurate measure of research quality?

No single metric measures research quality accurately. Each metric captures a different aspect of citation behavior, and all citation-based metrics have known limitations. Citation counts measure influence, not quality. They can be inflated by self-citation, distorted by review article bias, and skewed by field differences. Researchers should treat metrics as useful but imperfect tools and use multiple metrics together when evaluating journals or researchers, rather than relying on any single number. The h-index is the most widely cited researcher-level metric and the impact factor is the most widely cited journal-level metric, but neither alone provides a complete picture of academic impact.


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