This map visualization puts journals, which frequently cite each other, closer together. You can drag the white magnification lens around to enlarge a part of the map for closer inspection. Clicking one of the nodes will highlight all its connections. If a journal is selected, the node sizes represent the relative amount of citation flow (incoming and outgoing) with respect to the selection; otherwise, they are scaled by their Eigenfactor® Score.
We use a subset of the citation data from Thomson Reuters' Journal Citation Reports
1997–2005. The complete data aggregate, at the journal level, approximately 60,000,000 citations from more than 7000 journals over the past decade. For an interesting subset, we select journals ordered by their Article Influence®
in 2005, but include no more than 25 journals from a single field. To make the subset coherent, we make sure that selected journals are included all years and that we cover the 10 journals with highest Eigenfactor
® score. To cluster the networks, we use the information-theoretic method presented in Maps of information flow reveal community structure in complex networks
(PNAS 105, 1118 (2008)
), which can reveal regularities of information flow across directed and weighted networks.