Journal impact and proximity: An assessment using bibliographic features

Journals in the " Information Science and Library Science " category of Journal Citation Reports (JCR) were compared using both bibliometric and bibliographic features. Data collected covered: journal impact factor, number of issues per year, number of authors per paper, longevity, editorial board membership, frequency of publication, number of databases indexing the journal, number of aggregators providing and journal statement of scope. Three features significantly correlated with journal impact factor: number of editorial board members and number of Journal Citation Report categories in which a journal is listed correlated positively; journal longevity correlated negatively with journal impact factor. Co‐word analysis of journal descriptions provided a proximity clustering of journals, which differed considerably from the clusters based on editorial board membership. Finally, a multiple linear model was built to predict the journal impact factor based on all the collected bibliographic features.