Eigenfactor and Article Influence Score
The Eigenfactor Score and its per-article companion, the Article Influence Score, rank scholarly journals by treating the citation network as a system in which a citation from a prestigious journal counts for more than a citation from an obscure one. Carl Bergstrom introduced the Eigenfactor in 2007 using the same recursive idea behind Google's PageRank: a journal is important if it is cited by other important journals. The score is computed as the stationary distribution of a random walk over the journal-to-journal citation matrix, so it captures not just how often a journal is cited but where those citations come from. The Eigenfactor measures a journal's total influence and therefore scales with size; dividing by the journal's share of articles yields the Article Influence Score, a per-paper measure comparable to a normalized impact factor. West, Bergstrom and Bergstrom set out the full network methodology in 2010.
Record di origine
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- Bergstrom, C. T. (2007). Eigenfactor: Measuring the value and prestige of scholarly journals. College & Research Libraries News, 68(5), 314-316. · DOI 10.5860/crln.68.5.7804
- West, J. D., Bergstrom, T. C., & Bergstrom, C. T. (2010). The Eigenfactor Metrics: A network approach to assessing scholarly journals. College & Research Libraries, 71(3), 236-244. · DOI 10.5860/0710236
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