Skip to main content
# Scholarly Impact Metrics

## Impact metrics

## Eigenfactor

PubMed is a valuable tool for searching the biomedical literature, but it can be hard to determine which of a long list of results are likely to be the most important or the most credible. Eigenfactorizer is a free plugin for the Chrome browser that color-codes the results of your pubmed search results according to the Article Influence score of the journals in which they appear. Using this tool, it is easy to quickly filter search results visually. Because of data usage restrictions, Eigenfactorize does not use the standard Article Influence scores based on the Thomson-Reuters JCR data. Instead, the tool uses Pubmed-Article Influence scores, which are calculated using the Pubmed Central citation network of 16 million citations in the biomedical sciences

*c*_{avg}

is the average number of citations received by an author's articles.

*h*index

is defined as the maximum number of articles *h* such that each has received at least *h* citations (Hirsch, 2005). The *h* index is the most widely adopted impact metric. It summarizes the impact of a scholar's career using a single number without any threshold.

*h**m*index

attempts to apportion citations fairly for papers with multiple authors (Schreiber, 2008). It counts the papers fractionally according to the number of authors. This yields an effective rank, which is utilized to define *h**m* as the maximum effective number of papers that have been cited *h**m* or more times.

*h**f*index

was proposed as a universal variant of *h* (Radicchi, Fortunato, & Castellano, 2008). The number of citations *c* received by each paper is normalized by the average number of citations *c*0 for papers published in the same year and discipline. The rank of each paper *n* is rescaled by the average number *n*0 of papers per author written in the same year and discipline. The *h**f* index of the author is the maximum rescaled rank *h**f* such that each of the top *h**f* papers has at least *h**f* rescaled citations.

*h**s*index

is proposed here as a normalization of the *h* index by the average *h* of the authors in the same discipline. Numerical tests show that the distribution of *h* is not scale-free and therefore the mean is well defined. Despite its simplicity, we are not aware of this metric being previously defined in the literature. Note that within a discipline, *h**s*produces the same ranking as *h*. Therefore, *h**s* is very similar to the percentile score but slightly easier to compute. Percentiles have been proposed for normalization of journal impact factors (Leydesdorff & Bornmann, 2011).

**Redner's index ctotal1/2**

is defined as the square root of the total number of citations received by an author's articles (Redner, 2010)

*g*index

is the highest number *g* of papers that together receive *g*^{2} or more citations (Egghe, 2006). It attempts to mitigate the insensitivity of the *h* index to the number of citations received by highly cited papers.

*i*_{10}

is proposed by Google and is defined as the number of articles with at least ten citations each (Google scholar citations open to all, 2011).

**Batista's h_{i}_{,norm}**

involves normalizing the total number of citations in the *h*-core (the papers that contribute to the *h* index) by the total number of authors contributing to them. The resulting *h** _{i}* of each author is then normalized by the average

**New crown indicator(c/c0)avg**

was proposed by Lundberg (2007) as the item oriented field-normalized citation score (FNCS) and implemented by Waltman, van Eck, van Leeuwen, Visser, and van Raan (2011). It is calculated as the average field-normalized number of citations *c*/*c*_{0} across an author's publications.

**Seton Hall University**- 400 South Orange Avenue
- South Orange, NJ 07079
- (973) 761-9000

Follow SHU_Libraries