Impact Factor – Science Journal Assessment Metrics

Impact factor of a journal is widely considered as a yardstick for its scholarly status. Though there is no consensus on what is a good impact factor, some well-regarded journals such as Journal of Biological Chemistry and American Journal of Physiology journals are ranked only in single digits.  Journals such as Nature, Cell and Science are consistently ranked above 20 for the past several years. Journal publishers and editors work hard to increase the impact factor of their journals.  Scientists compete to get their manuscripts published in journals with high impact factors. 

The impact factor, originally devised by Eugene Garfield, at the Institute for Scientific Information, uses a formula that takes into account, number of papers published in the current year and number of citations in the current and past year.  The formula for impact factor is not a secret, nor the metrics used to determine the annual impact factor for each journal. Thomson Reuters publish these details for each of the indexed journals, on their subscription-controlled website.

The formula used to calculate a journal impact factor is:  (n1+n2)n.
Where, n=total number of citable articles published in the previous two years (For example, to calculate impact factor of a journal in 2013, articles published in that journal in the years 2011 and 2012 are considered); n1= number of citations in articles published in any journal in the year under consideration for articles published in that journal in the previous year (Using the above example, number of citations in 2013 for articles published in 2012); n2=number of citations in articles published in any journal in the year under consideration for article published in that journal two years ago (For example, number of citations in 2013 for articles published in 2011).

The algorithm used for determining page rank of a webpage, by google, is similar to the method used in determining impact factor.

Though use of impact factor has been criticized, it is a metric widely used by scientists and funding agencies to assess scholarly contributions.

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