Reviewer Finder

Reviewer Finder

Finding suitable peer reviewers for a manuscript can be a challenging, time-consuming task. We want to help make the process easier and faster for our editors. Reviewer Finder is an exciting tool that reduces the manual work involved in finding relevant reviewers. 

To use the tool, simply enter information about the manuscript you are sending out for review into the Reviewer Finder and it will return a list of possible reviewers.

Get Started:

Enter as much information as possible

Fields you can fill-out include:

  • Manuscript Title
  • Author Name(s)
  • Abstract
  • Keywords

Check the suggestions

The matching algorithm returns researchers who have a publishing profile similar to that of the manuscript author(s). Go through the comprehensive list of reviewer names that are sorted by relevance. You will be able to expand each name to learn more about the person’s research background.

Helpful Features

  • Reviewer Finder will flag conflicts of interest related to authorship, co-authorship, and institutional affiliations
  • Save searches so that you can refer back to the results for similar papers

Frequently Asked Questions

How does Reviewer Finder intend to help?

We help by searching a pool of data for suitable reviewers (hopefully we can find contacts that you do not know) and providing information about their profile, past publications, and possible conflicts of interests to help you make a decision on whether to invite the reviewer to review or not.

What data source is the tool searching?

The tool is searching data from Web of science (provided by Clarivate Analytics) through Target Author Data Graph.

Clarivate Analytics ISI Web of Science - Web of Science is highly comprehensive and multidisciplinary in its journal coverage. Sources include leading STM, humanities, and social science journals.

How does the search algorithm work?

The matching process uses two concepts to create the matching algorithm.

  • Data Graph: A data graph is constructed from a data source (Web of Science) to create a unique list of authors, their organizational details and publishing history.
  • Suggestion Engine: Entering basic manuscript attributes into the Reviewer Finder tool, such as Title, Abstract text, Keywords and names of the Authors causes the suggestion engine to recommend authors that it calculates will be a good match for peer review.

The software defines a good match to be someone who has a similar publishing profile to that of the manuscript author. Therefore the algorithm attempts to find individuals who have published material that most closely resembles that of the original author.

What should I do once I’ve finished searching?

We present the data as we find it and suggest that you confirm there aren’t any conflicts of interests using your usual methods until you’re confident our tool delivers results you’re happy with.

What should I do if I have a question?

Please send your questions to and we will be sure to provide an answer!