A Large-Scale Analysis of Impact Factor Biased Journal Self-Citations.

ABSTRACT: Based on three decades of citation data from across scientific fields of science, we study trends in impact factor biased self-citations of scholarly journals, using a purpose-built and easy to use citation based measure. Our measure is given by the ratio between i) the relative share of journal self-citations to papers published in the last two years, and ii) the relative share of journal self-citations to papers published in preceding years. A ratio higher than one suggests that a journal's impact factor is disproportionally affected (inflated) by self-citations. Using recently reported survey data, we show that there is a relation between high values of our proposed measure and coercive journal self-citation malpractices. We use our measure to perform a large-scale analysis of impact fa

SUBMITTER: Chorus C 

PROVIDER: S-EPMC4999059 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature