Best of both worlds? Simultaneous evaluation of researchers and their works

TL;DR

This paper introduces a dual scoring system based on a modified CITEX algorithm to evaluate both researchers and their publications simultaneously using citation and author data.

Contribution

It extends the CITEX algorithm to jointly assess researcher importance and paper quality through a novel iterative HITS-like approach.

Findings

Effective in ranking authors and papers simultaneously

Validated on over 200,000 publications from 1980-2012

Demonstrates the dual evaluation system's robustness

Abstract

This paper explores a dual score system that simultaneously evaluates the relative importance of researchers and their works. It is a modification of the CITEX algorithm recently described in Pal and Ruj (2015). Using available publication data for $m$ author keywords (as a proxy for researchers) and $n$ papers it is possible to construct a $m \times n$ author-paper feature matrix. This is further combined with citation data to construct a HITS-like algorithm that iteratively satisfies two criteria: first, \emph{a good author is cited by good authors}, and second, \emph{a good paper is cited by good authors}. Following Pal and Ruj, the resulting algorithm produces an author eigenscore and a paper eigenscore. The algorithm is tested on 213,530 citable publications listed under Thomson ISI's "\emph{Information Science \& Library Science}" JCR category from 1980--2012.