CITEX: A new citation index to measure the relative importance of authors and papers in scientific publications
This addresses the need for objective measures of author reputation and paper impact in scientific publications, though it appears incremental as it builds on existing citation analysis methods.
The authors tackled the problem of evaluating researcher performance and paper impact by proposing CITEX, a new citation index that assigns normalized scores to both authors and papers, with results showing it provides far more accurate scores compared to traditional metrics.
Evaluating the performance of researchers and measuring the impact of papers written by scientists is the main objective of citation analysis. Various indices and metrics have been proposed for this. In this paper, we propose a new citation index CITEX, which gives normalized scores to authors and papers to determine their rankings. To the best of our knowledge, this is the first citation index which simultaneously assigns scores to both authors and papers. Using these scores, we can get an objective measure of the reputation of an author and the impact of a paper. We model this problem as an iterative computation on a publication graph, whose vertices are authors and papers, and whose edges indicate which author has written which paper. We prove that this iterative computation converges in the limit, by using a powerful theorem from linear algebra. We run this algorithm on several examples, and find that the author and paper scores match closely with what is suggested by our intuition. The algorithm is theoretically sound and runs very fast in practice. We compare this index with several existing metrics and find that CITEX gives far more accurate scores compared to the traditional metrics.