Natural Language Processing Approach for Classification of Archetypes Using Text on Business Environments

Abstract

Organizations increasingly offer resources to improve performance, minimize costs, and achieve better results. An organization is the individuals who work or provide services in it. Therefore, good organizational performance directly results from the good work of its collaborators. Identifying the archetype in the business environment can combine individuals with companies, which can improve the organizational environment and enhance the development of the individual. A person leaves traces of his behavior in what he produces, such as videos and texts. Some studies point to the possibility of identifying a behavioral profile from a textual production. In this work, we seek to identify the archetype of individuals within the business environment based on their curriculum texts. We combine the behavioral profile assessment (BPA) archetypes (Planner, Analyst, Communicator, and Executor) with 26, 636 curriculum to apply machine learning models. For this task, we used classification and regression approaches. The main algorithm used for the approaches was the SVM. The results suggest that the archetypes are better modeled using regression techniques, obtaining an MSE of 4.49 in the best case. We also provide a visual explanation example to understand the model outputs.