BIP! Finder for COVID-19
23-03-2020
BIP! Finder (bip.imsi.athenarc.gr) is a tool that assists the discovery of valuable publications. This tool supports ranking and comparing of scientific articles based on their popularity (short-term impact) or influence (long-term impact), while it provides useful features like intuitive infographics for each article and a mechanism of bookmarks.
Measuring impact of a scientific article is not a trivial task, and we may easily stumble into pitfalls along the way. It is an oversimplification to assume that there is a single, one-size-fits-all publication impact measure. In fact, such an impact may have several aspects that should be captured and understood in many different ways.
For example, a researcher often needs to search for the most “popular” articles in a field, i.e., those which are currently the focal point of the scientific community. On the other hand, a researcher may be interested in collecting “influential” papers for a field, i.e., those which have strongly shaped the field. Each of those impact aspects of a paper, i.e., popularity and influence, can be estimated by performing a different type of link analysis on the underlying citation network.
In BIP! Finder, influence is calculated using PageRank while popularity is calculated by executing TAR-RAM on the citation network.
BIP! Finder for COVID-19 (bip.covid19.athenarc.gr) is a special version of BIP! Finder to ease the exploration of COVID-19-related literature, based on a subset of the CORD-19 dataset* released by Semantic Scholar. The short-term & long-term impact (citation popularity/reading hype & influence, respectively) of the corresponding publications has been calculated using data from the underlying citation network (PMC and OpenCitations COCI) and Mendeley.
The dataset containing the calculated impact scores are openly available at the zenodo repository: https://doi.org/10.5281/zenodo.3723282.