It is possible to study the reviews-based dataset. The validity of this paradigm was demonstrated by our data analysis. The data taken from the Twitter reviews (Myer-Briggs) dataset is subjected to behaviour analysis. To determine the user's remark, the data is evaluated. We want to use data-driven marketing technologies including supervised machine learning models, natural language processing, along with information visualisation. Logistic Regression is one of the classification techniques on which the system was constructed. The current issues with each topic are examined before the most recent fixes are provided and debated. The findings from the experiment demonstrate the accuracy, precision, recall, and F1 score. Following that, we can use the Twitter API to forecast the personality. It illustrates how openness is compared

Machine Learning, Natural Language Processing, Personality Prediction, Myer-Briggs, Behaviour Analysis