Screening articles by citation reputation

TL;DR

This paper presents a new method called reputable citations (RC) to evaluate the true influence of research papers by separating popularity from genuine impact, using citation data and institutional prestige.

Contribution

The paper introduces RC scores that distinguish researcher influence beyond citation counts, providing a nuanced tool for screening and identifying influential research.

Findings

RC scores differentiate influence from popularity.

Peer-acknowledged researchers often rank higher in RC scores.

High citation counts do not always indicate genuine influence.

Abstract

We introduce reputable citations (RC), a method to screen and segment a collection of papers by decoupling popularity and influence. We demonstrate RC using recent works published in a large set of mathematics journals from Clarivate's Incites Essential Science Indicators, leveraging Clarivate's Web of Science for citation reports and assigning prestige values to institutions based on well-known international rankings. We compare researchers drawn from two samples: highly cited researchers (HC) and mathematicians whose influence is acknowledged by peers (Control). RC scores distinguish the influence of researchers beyond citations, revealing highly cited mathematical work of modest influence. The control group, comprising peer-acknowledged researchers, dominates the top tier of RC scores despite having fewer total citations than the HC group. Influence, as recognized by peers, does not always correlate with high citation counts, and RC scores offer a nuanced distinction between the two. With development, RC scores could automate screening of citations to identify exceptional and influential research, while addressing manipulative practices. The first application of RC reveals mathematics works that may be cited for reasons unrelated to genuine research advancements, suggesting a need for continued development of this method to mitigate such trends.