ReviewerNet: A visualization platform for the selection of academic reviewers.

• An integrated visualization of scholarly data can support the academic reviewer search process. • The visualization of scholarly data helps to avoid conflicts of interest and to build a fairly distributed pool of reviewers. • A well-combined visualization of citations and co-authorship relations only, can reduce the need for complicated content analysis techniques. • The platform evaluation with members from the Computer Graphics community demonstrated the improvement on the traditional process for searching reviewers. • The evaluation confirmed that users were able to get acquainted with the system with a very limited training. 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 pertinent papers; ReviewerNet supports the construction of such set of papers, by visualizing and exploring a literature citation network. The system helps journal editors and Program Committee members to select reviewers that do not have any conflict-of-interest and are representative of different research groups, by visualising the careers and co-authorship relations of candidate reviewers. The system is publicly available, and is demonstrated in the field of Computer Graphics. [ABSTRACT FROM AUTHOR]