Where Should I Submit My Work for Publication? An Asymmetrical Classification Model to Optimize Choice

Abstract

Choosing a journal to publish a work is a task that involves many variables. Usually, the authors' experience allows them to classify journals into categories, according to their suitability and the characteristics of the article. However, there are certain aspects in the choice that are probabilistic in nature, whose modelling may provide some help. Suppose an author has to choose a journal from a preference list to publish an article. The researcher is interested in publishing the paper in a journal with a rank number less than or equal to k. For this purpose, a simple classification model is presented in order to choose the best journal from the list, from which some fundamental consequences can be deduced and simple rules derived. For example, if the list contains 100 journals and is ordered using 2-year Impact Factor, the rule "send to the journal at the k − 10 position" is adequate.