The Eigenfactor (EF) is an overall rating of the importance of a scientific journal whereby all articles published in a journal during a year are taken in to consideration when making the calculation. What counts in the Eigenfactor is the size of the journal, or how many articles a journal publishes. With all else equal, a journal's Eigenfactor score doubles when it doubles in size. The Eigenfactor is scaled so that all the publications that feature in the Journal Citation Reports (JCR) have a summed EF of one hundred. The calculation of the Eigenfactor for journals is based on the PageRank algorithm, which enables determining the value of the journal that is citing the article, and citations are given different weight according to how high the EF score of the journal is. The EF score is calculated by counting all citations from five years after the article was published, and not just citations from a specific category of journals. In addition to scientific journals, the EF takes into consideration citations in newspaper articles, doctoral theses and books etc. In this way, one can get a fairer estimation for journals situated in the middle ground between scientific disciplines. It also takes into account different citation norms which enhances the comparability of journals from different scientific areas.
The scholarly literature forms a vast network of academic papers connected to one another by citations in bibliographies and footnotes. The structure of this network reflects millions of decisions by individual scholars about which papers are important and relevant to their own work. Therefore within the structure of this network is a wealth of information about the relative influence of individual journals, and also about the patterns of relations among academic disciplines.
Borrowing methods from network theory, the Eigenfactor score ranks the influence of journals much as Google's PageRank algorithm ranks the influence of web pages. By this approach, journals are considered to be influential if they are cited often by other influential journals. Iterative ranking schemes of this type, known as eigenvector centrality methods, are notoriously sensitive to "dangling nodes" and "dangling clusters": nodes or groups of nodes which link seldom if at all to other parts of the network. Eigenfactor algorithm modifies the basic eigenvector centrality algorithm to overcome these problems and to better handle certain peculiarities of journal citation data.
The Eigenfactor ranking system accounts for difference in prestige among citing journals, such that citations from Nature or Cell are valued highly relative to citations from third-tier journals with narrower readership. The Eigenfactor score also adjusts for differences in citation patterns among disciplines.
The Eigenfactor score is additive: to find the Eigenfactor of a group of journals, simply sum the Eigenfactors of each journal in the group.
The Eigenfactor scores for journals are available at http://www.eigenfactor.org/. Thomson Reuter's Journal Citation Reports also publishes Eigenfactor scores in edition 2007 and later at http://www.isiknowledge.com/JCR.
Details of the calculation of the Eigenfactor score are available at http://www.eigenfactor.org/methods.pdf
A diagram of Eigenfactor metrics calculation.