The x-index: A new citation-distance-based index to measure academic influence

TL;DR

The paper introduces the x-index, a new citation-distance-based metric for assessing academic influence, which improves discrimination over existing indices like the c-index, h-index, and g-index.

Contribution

It proposes the x-index that weights citations by their distance, addressing limitations of the c-index and enhancing measurement accuracy of academic impact.

Findings

x-index has stronger discriminatory power than c-index, h-index, and g-index.

Theoretical and empirical analyses validate the effectiveness of the x-index.

Analysis of citation and collaboration networks supports the proposed metric.

Abstract

An important issue in the field of academic measurement is how to evaluate academic influence scientifically and comprehensively, which can help government and research organizations better allocate academic resources and recruit researchers. It is generally accepted that using weighted citations to measure academic influence is more reasonable than treating all citations equally. Given the limitations of the existing c-index, the first index in bibliometric literature that measures output based on the quantity and quality of received citations, we propose the x-index, which assigns weight to each citation according to its distance. By defining collaboration distance and citation distance, we first analyze the properties of the collaboration network and citation distance, then perform theoretical and empirical analyses on c-index to reveal its shortcomings, finally, we suggest the x-index and conduct experiments and analysis on the x-index. Experimental results demonstrate that compared with the c-index, h-index, and g-index, the x-index shows a stronger discriminatory power.