เปรียบเทียบวิธี

	Source Normalized Impact per Paper (SNIP)	Eigenfactor and Article Influence Score
สาขาวิชา	บรรณมิติ	บรรณมิติ
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	2010	2007
ผู้ริเริ่ม	Henk F. Moed; Ludo Waltman, Nees Jan van Eck, Thed van Leeuwen & Martijn Visser	Carl T. Bergstrom; Jevin D. West, Theodore C. Bergstrom & Carl T. Bergstrom
ประเภท	Citation-potential-normalized journal impact pipeline	Eigenvector-based journal ranking pipeline
แหล่งต้นตำรับ	Moed, H. F. (2010). Measuring contextual citation impact of scientific journals. Journal of Informetrics, 4(3), 265-277.	Bergstrom, C. T. (2007). Eigenfactor: Measuring the value and prestige of scholarly journals. College & Research Libraries News, 68(5), 314-316.
ชื่อเรียกอื่น	SNIP, Citation Potential Normalization, Source-Normalized Journal Impact, Field-Normalized Citations per Paper	Eigenfactor Score, Article Influence Score, Network-Weighted Journal Prestige, Eigenvector Journal Metrics
ที่เกี่ยวข้อง	3	3
สรุป	The Source Normalized Impact per Paper, or SNIP, corrects a journal's citation rate for the citation behavior of its field so that journals in heavily cited and lightly cited disciplines can be compared on the same scale. Henk Moed introduced SNIP in 2010 with a distinctive twist: rather than classifying journals into predefined subject categories, it defines a journal's field from the bottom up as the set of papers that actually cite it, and it normalizes by that field's citation potential, measured from how long the citing papers' reference lists are. Fields whose authors cite many references generate more citations to go around, so a raw citation rate means different things in mathematics than in molecular biology. SNIP divides raw impact per paper by this citation potential to produce a field-corrected indicator. Ludo Waltman and colleagues revised the original formula in 2013 to remove some counterintuitive properties and improve stability; the revised SNIP is the version distributed in Scopus.	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.