Human Trait Analysis and Suggestions

Examining human characteristics provides a means of validating aspects associated with human identification. At the moment, big data-based platforms like X and Facebook are continuously and digitally logging every detail of human behavior. A Python-based system that can analyze human personality traits, emotions, interests, and behaviors from textual data and offer tailored recommendations based on the analysis was proposed in this paper. The goal of this research is to create a reliable system that can predict the Big by utilizing the power of machine Learning (ML) and natural language processing (NLP). This project's primary objective is to gather textual data from the user and use a machine Learning model that has been trained to predict their four personality traits: neuroticism, agreeableness, extraversion, conscientiousness, and openness. The main goal is to create an application that allows users to answer a series of questions that are then analyzed to determine their personality traits. The author of this paper processed and categorized the data using Natural Language Processing (NLP) techniques, XGBoost, Naive Bayes classifiers, logistic regression, and decision trees.