Journal-level metrics attempt to quantify a journal's impact by analyzing the citations arising from the articles it publishes.
Advantages: Journal metrics can give a sense of which journals are popular and/or respected within a specific field.
Disadvantages: These metrics effectively average the impact of a journal's articles and authors, so they hide variations among articles and authors. Journal metrics also are not generalizable across disciplines.
In a recent post on the Scholarly Open Access blog, Jeffrey Beall describes the recent proliferation of potentially bogus impact factor companies. It is important to evaluate the methodoloies used by organizations that produce journal rankings. Some rankings include a narrow lists of titles. Others have been known to award high impact factors to journals -- for a fee.
The Journal Citation Reports (JCR) Impact Factor is calculated by dividing the number of citations in a year by the total number of articles published in the two previous years. For example, an Impact Factor of 1.0 means that, on average, the articles published in a given journal 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.
The Eigenfactor, like the Impact Factor, starts with the citation data from Journal Citation Reports but has a more complicated algorithm. Journals are considered to be more influential if they are cited often by other influential journals. For example, citations from Nature or Cell are valued more highly than citations from journals with a narrower readership. Eigenfactor scores are also adjusted for differences in citation patterns across disciplines. They rely on data from five years, as compared to two for the Impact Factor.
Eigenfactor scores are scaled so that the sum of the Eigenfactor scores of all journals listed in Journal Citation Reports (JCR) is 100. In 2012, the journal Nature had the highest Eigenfactor score, with a score of 1.56539.