The volume of submissions for inclusion in scholarly journals offers new challenges for scholarly publishers. Even with recent advances in peer review and editorial management platforms, new solutions are emerging.
In the article, Kasenchak points out that using text analytics methods grounded in natural language processing (NLP) and other techniques to augment the submission review process can result in myriad benefits, such as leveraging taxonomy-based indexing terms to match manuscripts to appropriate reviewers and editors, preventing fraud by detecting machine-generated entries, screening for irreproducible research practices, and predicting the likelihood of acceptance by examining non-content factors.
Going forward, the newest advances in this arena will be driven by information professionals and professional services organizations. Because of their common goals with the scholarly publishers they serve, this will result in a better scenario.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.