Ensemble Machine Learning Models in Predicting Personality Traits and Insights using Myers-Briggs Dataset

Abstract

Personality prediction refers to the use of machine learning techniques to predict an individual's personality traits based on various sources of data, such as text, images, and social media usage Personality traits refer to persistent patterns of behaviors, thoughts, and feelings that differentiate one individual from another. The prediction of people’s personality traits based on their social media posts using various machine learning models. With the help of this model, a person’s personality can be classified based on the 16 categories of Myers-Briggs personality types. With the availability of a huge amount of data on human behavior and personality traits, it is possible to train a machine-learning model and predict the personality trait of a person. The ML model assesses the person based on their social media posts. The data consists of the posts from social media and the personality type to which a person belongs. The model will be using the NLTK library to assess and pre-process the data. Here a model has been based on built four machine learning models, which include logistic regression, support vector machines (SVM), nave Bayes, and random forest. Finally, we compare the machine learning model results to determine which one is best based on evaluation metrics (accuracy score, geometric mean score, ROC-AUC score). Furthermore, this can be used in the personalization of online advertising ads and campaigns. Also, it can be used by social media companies to attract users based on their personality traits and preferences.