Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Scholarly Impact and Citation Analysis

Tips and step-by-step directions on how to find citing articles, impact factors, and journal rankings.

h-index

The h-index is based on the highest number of papers included that have had at least the same number of citations. The value of h is equal to the number of papers (N) in the list that have N or more citations.

Thus, if the h-index for an author is 10, it means that of all his published articles, at least 10 have been cited 10 or more times.

The h-index was developed by J.E. Hirsch, a physicist at the University of California in San Diego.View Hirsch’s original paper.

Terms and Definitions

Terms and Definitions:

Journal Citation Reports (ISI)

Aggregate Impact Factor: The aggregate Impact Factor for a subject category is calculated the same way as the Impact Factor for a journal, but it takes into account the number of citations to all journals in the category and the number of articles from all journals in the category. An aggregate Impact Factor of 1.0 means that that, on average, the articles in the subject category published one or two years ago have been cited one time.

Article Influence Score: The Article Influence Score calculates measures the relative importance of the journal on a per-article basis. It is the journal's Eigenfactor Score divided by the fraction of articles published by the journal. That fraction is normalized so that the sum total of articles from all journals is 1. The mean Article Influence Score is 1.00. A score greater than 1.00 indicates that each article in the journal has above-average influence. A score less than 1.00 indicates that each article in the journal has below-average influence.

Eigenfactor Score: The Eigenfactor Score measures the number of times articles from the journal published in the past five years have been cited in the JCR year. Like the Impact Factor, the Eigenfactor Score is essentially a ratio of number of citations to total number of articles. However, unlike the Impact Factor, the Eigenfactor Score: Counts citations to journals in both the sciences and social sciences. Eliminates self-citations. Every reference from one article in a journal to another article from the same journal is discounted. Weights each reference according to a stochastic measure of the amount of time researchers spend reading the journal.

Immediacy Index: is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. The aggregate Immediacy Index indicates how quickly articles in a subject category are cited. The Immediacy Index is calculated by dividing the number of citations to articles published in a given year by the number of articles published in that year. Because it is a per-article average, the Immediacy Index tends to discount the advantage of large journals over small ones.

Journal Cited Half-Life: The median age of the articles that were cited in the JCR year. Half of a journal's cited articles were published more recently than the cited half-life. For example, in JCR 2001 the journal Crystal Research and Technology has a cited half-life of 7.0. That means that articles published in Crystal Research and Technology between 1995-2001 (inclusive) account for 50% of all citations to articles from that journal in 2001. Only journals cited 100 or more times in the JCR year have a cited half-life. A higher or lower cited half-life does not imply any particular value for a journal.

Journal Impact Factor: The journal impact factor measures the importance of a journal and "is a measure of the frequency with which the 'average article' in a journal has been cited in a particular year or period". The Impact Factor is calculated by dividing the number of citations in the JCR year by the total number of articles published in the two previous years. An Impact Factor of 1.0 means that, on average, the articles published one or two year ago have been cited one time. An Impact Factor of 2.5 means that, on average, the articles published one or two year ago have been cited two and a half times. Citing articles may be from the same journal; most citing articles are from different journals.

Median Impact Factor: is the median value of all journal Impact Factors in the subject category. The Impact Factor mitigates the importance of absolute citation frequencies. It tends to discount the advantage of large journals over small journals because large journals produce a larger body of citable literature. For the same reason, it tends to discount the advantage of frequently issued journals over less frequently issued ones and of older journals over newer ones. Because the journal impact factor offsets the advantages of size and age, it is a valuable tool for journal evaluation.

Scopus

SCImago Journal Rank (SJR):  is weighted by the prestige of a journal.  Subject field, quality and reputation of the journal have a direct effect on the value of a citation.  SJR also normalizes for differences in citation behavior between subject fields.  Four years of data are needed to calculate a SJR. Scopus' records complete citation data from 1996, so the first SJR value available is for 1999.

Source Normalized Impact per Paper (SNIP): Source Normalized Impact per Paper measures contextual citation impact by weighting citations based on the total number of citations in a subject field. Four years of data are needed to calculate a SNIP. Scopus' records complete citation data from 1996, so the first SJR value available is for 1999.

Publish or Perish metrics

Hirsch's h-index: Proposed by J.E. Hirsch in his paper An index to quantify an individual's scientific research output,arXiv:physics/0508025 v5 29 Sep 2005. It aims to provide a robust single-number metric of an academic's impact, combining quality with quantity.

Egghe's g-index: Proposed by Leo Egghe in his paper Theory and practice of the g-index, Scientometrics, Vol. 69, No 1 (2006), pp. 131-152. It aims to improve on the h-index by giving more weight to highly-cited articles.

Zhang's e-index: Publish or Perish also calculates the e-index as proposed by Chun-Ting Zhang in his paper The e-index, complementing the h-index for excess citations, PLoS ONE, Vol 5, Issue 5 (May 2009), e5429. The e-index is the (square root) of the surplus of citations in the h-set beyond h2, i.e., beyond the theoretical minimum required to obtain a h-index of 'h'. The aim of the e-index is to differentiate between scientists with similar h-indices but different citation patterns.

Contemporary h-index: Proposed by Antonis Sidiropoulos, Dimitrios Katsaros, and Yannis Manolopoulos in their paper Generalized h-index for disclosing latent facts in citation networks, arXiv:cs.DL/0607066 v1 13 Jul 2006. It aims to improve on the h-index by giving more weight to recent articles, thus rewarding academics who maintain a steady level of activity.

Age-weighted citation rate (AWCR) and AW-index: The AWCR measures the average number of citations to an entire body of work, adjusted for the age of each individual paper. It was inspired by Bihui Jin's note The AR-index: complementing the h-index, ISSI Newsletter, 2007, 3(1), p. 6. The Publish or Perish implementation differs from Jin's definition in that we sum over all papers instead of only the h-core papers.

Individual h-index (original): The Individual h-index was proposed by Pablo D. Batista, Monica G. Campiteli, Osame Kinouchi, and Alexandre S. Martinez in their paper Is it possible to compare researchers with different scientific interests?,Scientometrics, Vol 68, No. 1 (2006), pp. 179-189. It divides the standard h-index by the average number of authors in the articles that contribute to the h-index, in order to reduce the effects of co-authorship.

Individual h-index (PoP variation): Publish or Perish also implements an alternative individual h-index that takes a different approach: instead of dividing the total h-index, it first normalizes the number of citations for each paper by dividing the number of citations by the number of authors for that paper, then calculates the h-index of the normalized citation counts. This approach is much more fine-grained than Batista et al.'s; we believe that it more accurately accounts for any co-authorship effects that might be present and that it is a better approximation of the per-author impact, which is what the original h-index set out to provide.