New paper-by-paper classification for Scopus based on references reclassified by the origin of the papers citing them

TL;DR

This paper introduces a novel reference-based classification system for Scopus publications that considers citing papers' categories, allowing more flexible and potentially comprehensive reclassification compared to traditional journal-based methods.

Contribution

It presents a new multi-category classification approach based on citing papers' categories, improving coverage and consistency over existing systems.

Findings

The system can reclassify up to 100% of publications.

Multiple variants were tested, with U1-F-0.8 showing promising results.

The new system outperforms traditional journal-based classifications.

Abstract

A reference-based classification system for individual Scopus publications is presented which takes into account the categories of the papers citing those references instead of the journals in which those cited papers are published. It supports multiple assignments of up to 5 categories within the Scopus ASJC structure, but eliminates the Multidisciplinary Area and the miscellaneous categories, and it allows for the reclassification of a greater number of publications (potentially 100%) than traditional reference-based systems. Twelve variants of the system were obtained by adjusting different parameters, which were applied to the more than 3.2 million citable papers from the active Scientific Journals in 2020 indexed in Scopus. The results were analyzed and compared with other classification systems such as the original journal-based Scopus ASJC, the 2-generation-reference based M3-AWC-0.8 (\'Alvarez-Llorente et al., 2024), and the corresponding authors' assignment based AAC (\'Alvarez-Llorente et al., 2023). The different variants obtained of the classification give results that improve those used as references in multiple scientometric fields. The variation called U1-F-0.8 seems especially promising due to its restraint in assigning multiple categories, consistency with reference classifications and the fact of applying normalization processes to avoid the overinfluence of articles that have a greater number of references.