The citation chain: Eigenfactor maps the researchers citation trail and the amount of time he spends at each citation along the track.

Another way of mapping and ranking is developed, which ranks journals much as Google ranks websites; the Eigenfactor. This new concept and facility is developed as part of a non-commercial academic research project sponsored by the Bergstrom lab in the Department of follow the trailBiology at the University of Washington. They aim to develop novel methods for the F factor; ISi and NON-ISI combinedevaluating the influence of scholarly periodicals and for mapping the structure of academic research. The Eigenfactor score of a journal is an estimate of the percentage of time that library users spend with that journal. The Eigenfactor algorithm corresponds to a simple model of research in which readers follow chains of citations as they move from journal to journal. Imagine that a researcher goes to the library and selects a journal article at random. After reading the article, the researcher selects at random one of the citations from the article. She then proceeds to the journal that was cited, reads a random article there, and selects a citation to direct her to her next journal volume. The researcher does this ad infinitum. The amount of time that the researcher spends with each journal gives us a measure of that journal’s importance within network of academic citations. The amount of time that a researcher spends with each journal gives an estimate of the amount of time that real researchers spend with each journal. The developers of this new concept use mathematics to simulate this process.

Just to try I searched the Business category in the search option of this facility. As a result of this a list of 717 journals was presented. For all the journals the article influence was listed. The following screenshot gives an overview of the result:

Eigenfactor business category

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