Neural Networks in Predicting Myers Brigg Personality Type From Writing Style

Personality is the defining essence of an individual as it guides the way we think, act, and interpret external stimuli. Over the past century, aspects of personality have been studied from many angles whether through analyzing interpersonal relationships, team dynamics, and social networks or through works in neuroscience that reveal the biological underpinnings of personality traits. While many components of our personality remain consistent with time, behaviors are not as stable given they adapt to environmental situations and integrate habits that one accumulates throughout their life. Understanding the underlying essence of a person amidst the noise of behavior is a very highly sought out problem. Many studies have aimed to predict personality by analyzing patterns in ones behavior, pictures, and even handwriting. The brain regions that encode for various personality traits are often coupled with regions responsible with verbal and written communication. Furthermore, the advent of social media and an increasingly connected online community makes personalized textual data increasingly available. In this study, we hypothesize that an individuals writing style is largely coupled with their personality traits and present a deep learning model to predict Myers Briggs Personality Type through textual data from books. Developing an accurate model and opening this question of research would have significant implications in the business intelligence, relationship compatability analysis, and other fields in sociology.