Assessing impact and quality from local dynamics of citation networks
We show that essentially local dynamics of citation networks bring special information about the relevance/quality of a paper. Up to some rescaling, they exhibit universal behavior in citation dynamics: temporal patterns are remarkably consistent across disciplines, and uncover a prediction method for citations based on the structure of references only, at publication time. Above-average cited papers universally focus extensively on their own recent subfield – as such, citation counts essentially select what may plausibly be considered as the most disciplinary and normal science; whereas papers which have a peculiar dynamics, such as re-birthing scientific works – ‘rediscovered classics’ or ‘early birds’ – are comparatively poorly cited, despite their plausible relevance for the underlying communities. The “rebirth index” that we propose to quantify this phenomenon may be used as a complementary quality-defining criterion, in addition to final citation counts. âº We study relationships between impact and local, dynamical patterns of citation networks. âº Citation counts essentially captures normal science, from the recent past. âº Citation data immediately available at publication time has predictive properties. âº We define rebirth-index to quantitatively detect ‘sleeping beauties’ or ‘early birds’. âº ‘Re-birthing’ articles have significantly poorer-than-average citation metrics.