cc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications

Abstract

A new framework is proposed for the calculation of impact factor ratings of research publications (articles). For each one article, a corresponding citations graph is constructed in the form of a relational table. The impact factor is calculated by considering not only the citations made directly to an article, but also citations made to the corresponding citing article(s). In this respect, an improved algorithm is utilized, namely one that traverses all the threads in the citations graph, in an attempt to improve the degree of fairness in assigning credit for the quality of each one article. When two articles have an equal number of (direct) citations, the one that has triggered more research activity (i.e. its citing articles attract a larger number of citations at subsequent levels in the citations graph) is assigned a higher impact factor rating and, consequently, is ranked to be better.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 20 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.