ReviewerNet: Visualizing Citation and Authorship Relations for Finding Reviewers
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.
Cite
@article{arxiv.1903.08004,
title = {ReviewerNet: Visualizing Citation and Authorship Relations for Finding Reviewers},
author = {Mario Salinas and Daniela Giorgi and Paolo Cignoni},
journal= {arXiv preprint arXiv:1903.08004},
year = {2019}
}
Comments
11 pages, 5 figures