MBTI-BASED PERSONALITY PREDICTION FROM TEXT USING MACHINE LEARNING TECHNIQUES

Abstract

Personality prediction research seeks to define and comprehend the nuanced differences in human behavioural tendencies, thought patterns, and emotional expressions. Utilizing an array of methodologies, including psychological assessments, behavioural observations, and computational modelling, researchers aim to anticipate and clarify an individual's distinctive personality traits and characteristics. Natural Language Toolkit (NLTK) approaches are used to preprocess and translate text data into numerical features that can be predicted by machine learning models. The aim of this work is to predict the personality type of an individual linked to their posts and to explore the relevance of the test in the study and categorization of human behaviour using learning models. With the aid of a machine learning model and dataset, the main objective of this research is to determine a person's Myers-Briggs Type Indicator (MBTI) personality type based on their postings. This involves utilizing various methodologies, including psychological assessments and computational modelling, to analyse and classify the unique personality traits and characteristics associated with each MBTI type. The research aims to contribute valuable insights into understanding human behaviour and leveraging machine learning for predictive personality analysis.