Sentiment analysis using machine learning: Applied to job interviews - Martínez Zarate, Julio César; Mateus, Sandra Patricia (TECHNO REVIEW. International Technology, Science and Society Review /Revista Internacional de Tecnología, Ciencia y Sociedad, 2019)
In this work, a sentiment analysis model applied to job interviews using machine learning is proposed. A register of gaze fixations was made with "Eye Tracking" techniques. Subsequently, different algorithms of machine learning for sentiment analysis were analyzed, selecting supervised machine learning with Artificial neural networks. Once the model is obtained, it can be applied to job interviews for the staff pick in the organizations, through the interpretation of the eye accessing cues. The job interview is an important process in the staff pick with multiple purposes, including evaluating personality.