Scholars have combined standard research metrics, like scholarly output and citation counts, into formulas to measure and assess author and journal impact in new ways. Some of these metrics include:
On this page you will learn what these metrics measure, how to calculate these metrics, and databases and resources to look up each metric in.
Calculating metrics can sometimes be complicated and confusing. This table provides a brief introduction to each calculation and what it means.
Metric |
Website |
Calculation |
Meaning |
Impact Factor |
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Use a two-year period to divide the number of times articles were cited by the number of articles that were published Example: 200 = the number of times articles published in 2018 and 2019 were cited by indexed journals during 2020. 73 = the total number of "citable items" published in 2018 and 2019.
200/73 = 2.73 2020 impact factor |
Impact factor reflects only on how many citations on a specific journal there are (on average). A journal with a high impact factor has articles that are cited often. |
h-index |
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1) Create a list of all of your publications. organize articles in descending order, based on the number of times they have been cited. 2) Look down through the list to figure out at what point the number of times a publication has been cited is equal to or larger than the line (or paper) number of the publication. *please remember that many databases will give you this number; this is only if you'd like to calculate it manually. You can also often find calculators online. *graphic courtesy of the University of Waterloo Libguide |
The h-index focuses more specifically on the impact of only one scholar instead of an entire journal. The higher the h-index, the more scholarly output a researcher has. |
g-index |
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Given a list of articles ranked in decreasing order of the number citations that they received, the g-index is the largest unique number to the extent that the top g articles received together is at least g2 citations. |
The g-index can be thought of as a continuation of the h-index. The difference is that this index puts more weight on highly-cited citations. The g-index was created because scholars noticed that h-index ignores the number of citations to each individual article beyond what is needed to achieve a certain h-index. This number often complements the h-index and isn't necessarily a replacement. |
Eigenfactor score |
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The Eigenfactor score is calculated by eigenfactor.org. However, their process is very similar to calculating impact factor and they pull their data from the JCR as well. The major difference is that the Eigenfactor score deletes references from one article in a journal to another in the same journal. This eliminates the problem of self-citing. The Eigenfactor score is also a five-year calculation. More information can be found in the JCR glossary. |
A high Eigenfactor score signals that the journal does not self-cite and controls the network of that discipline. It's useful to look at scholar's h-index as well as the Eigenfactor score of the journals they publish in in order to get a broad sense of their impact as a researcher. |
Altmetric PlumX
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Altmetric scores are usually calculated by companies. This means that they can't be calculated manually. |
Different sources go into altmetrics calculations, depending on the company and the information that they are using. But in general, a high altmetric score indicates that an item has received a lot of attention and it has also received what that company has decided is "quality" attention (i.e. a news post might be more valuable than a twitter mention). Remember that attention doesn't necessarily indicate that the article is important or even of quality. That's why it's useful to use altmetrics and traditional research metrics together. |