Novelpy: A Python package to measure novelty and disruptiveness of bibliometric and patent data
Digital Libraries
2022-11-21 v1
Abstract
Novelpy (v1.2) is an open-source Python package designed to compute bibliometrics indicators. The package aims to provide a tool to the scientometrics community that centralizes different measures of novelty and disruptiveness, enables their comparison and fosters reproducibility. This paper offers a comprehensive review of the different indicators available in Novelpy by formally describing these measures (both mathematically and graphically) and presenting their benefits and limitations. We then compare the different measures on a random sample of 1.5M articles drawn from Pubmed Knowledge Graph to demonstrate the module's capabilities. We encourage anyone interested to participate in the development of future versions.
Cite
@article{arxiv.2211.10346,
title = {Novelpy: A Python package to measure novelty and disruptiveness of bibliometric and patent data},
author = {Pierre Pelletier and Kevin Wirtz},
journal= {arXiv preprint arXiv:2211.10346},
year = {2022}
}