An Algorithm to Determine Peer-Reviewers

TL;DR

This paper introduces an automated, efficient algorithm leveraging co-authorship networks and a particle-swarm method to identify suitable peer reviewers, potentially enhancing transparency and objectivity in the peer-review process.

Contribution

It presents a novel, computationally efficient algorithm that automatically selects appropriate reviewers and detects conflicts of interest without human intervention.

Findings

Validated using referee bid data from 2005 Digital Libraries conference.

Can identify conflicts of interest automatically.

Provides weighted expertise scores for reviewers.

Abstract

The peer-review process is the most widely accepted certification mechanism for officially accepting the written results of researchers within the scientific community. An essential component of peer-review is the identification of competent referees to review a submitted manuscript. This article presents an algorithm to automatically determine the most appropriate reviewers for a manuscript by way of a co-authorship network data structure and a relative-rank particle-swarm algorithm. This approach is novel in that it is not limited to a pre-selected set of referees, is computationally efficient, requires no human-intervention, and, in some instances, can automatically identify conflict of interest situations. A useful application of this algorithm would be to open commentary peer-review systems because it provides a weighting for each referee with respects to their expertise in the domain of a manuscript. The algorithm is validated using referee bid data from the 2005 Joint Conference on Digital Libraries.