Personality Prediction Using Machine Learning and Social Media Data: A Myers-Briggs Approach

With the explosive growth of user-generated content on social media, there is a rising interest in utilizing digital footprints to infer personality traits. This study explores how social media text can be analyzed using Natural Language Processing (NLP) and machine learning to predict an individual’s personality, focusing on the Myers-Briggs Type Indicator (MBTI) framework. Leveraging linguistic and behavioral features extracted from social media content, we apply Support Vector Machines (SVM) and Random Forest algorithms to classify users into MBTI personality types. Our approach highlights the scalability and potential of automated personality assessment in domains such as targeted marketing, recruitment, and mental health.