Personality identification by deep learning

Abstract

In recent years, that researchers in psycho-social fields classify the personalities according to different criterias, is one of the most interesting studies. In the viewpoint of the artificial intelligence researches, it is considered that analyzing the personalities will provide achieving realistic character modellings and realizing more intelligent systems via engineering disiplines in future. Beside of methodological gaps and conceptual uncertainities, insufficiencies in the mathematical modellings make developing computational algorithm difficult for this issue. These algorithms can be developed by present numerical or machine learning based methods in the literature. It can be realized by a hybrid method as composition of them. Numerical methods with linear or nonlinear system can also be suitable. From the standpoint of uncertainities, probabilistic (Bayesian, Monte Carlo, etc.) or fuzzy approaches can elaborate the modelling. Machine learning based methods (Markovian, support vector machines, Boltzman machines or artificial neural networks, etc.) can provide benefit to this kind of the study. In this study, we propose deep neural network based personality identification system with dataset which is composed from given responses to a questionaire prepared as suitable to the purpose. Our approach is verified with the classification results related to this.