ReviewerNet: Visualizing Citation and Authorship Relations for Finding Reviewers

TL;DR

ReviewerNet is an interactive visualization tool designed to assist in selecting unbiased, well-distributed reviewers for academic papers by exploring citation networks and co-authorship relations.

Contribution

It introduces a novel system that visualizes citation and authorship networks to improve reviewer selection processes in academia.

Findings

System effectively visualizes citation networks and co-authorship relations.

Evaluated positively by experienced researchers in Computer Graphics.

Helps identify suitable reviewers with minimal conflicts of interest.

Abstract

We propose ReviewerNet, an online, interactive visualization system aimed to improve the reviewer selection process in the academic domain. Given a paper submitted for publication, we assume that good candidate reviewers can be chosen among the authors of a small set of relevant and pertinent papers; ReviewerNet supports the construction of such set of papers, by visualizing and exploring a literature citation network. Then, the system helps to select reviewers that are both well distributed in the scientific community and that do not have any conflict-of-interest, by visualising the careers and co-authorship relations of candidate reviewers. The system is publicly available, and it has been evaluated by a set of experienced researchers in the field of Computer Graphics.