BIP Finder 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 currently contains data for more than 45M articles and more than 447M citations. For each article, BIP! Finder's database contains some common metadata (e.g., its DOI, author list, publication year and venue, etc.) along with its citations. These citations are used to construct the citation network of the stored scientific articles. Citation data are gathered from OpenCitations while article metadata are collected from Crossref and Open Academic Graph . All impact aspect scores measured by us can be retrieved via our public API .
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