Unmasking The Enigma:Exploring Personality Traits Using Social Media Text

In this paper personality is an important parameter as it differentiates various individuals from another. Predicting personality has many applications in real world. The main objective of this project is to take textual data as input from the user and then run the trained machine learning model on this data to predict his four personality traits which are Introversion vs Extroversion, Sensing vs Intuition, Thinking vs Feeling, Judging vs Perceiving.The main objective is to build an application where users can answer the questions which are processed and analyzed to output his personality traits. The output is a string of four characters where each character determines a personality trait, total of sixteen personality types are possible.The Machine learning model Random Forest Classifier is used to classify the text and output four personality traits. Processing of large textual data is to be done using Natural Language Processing (NLP) techniques with the help of NLTK libraries to process and categorize the data. In order to increase the performance of the model hyper parameter tuning along with cross fold validations is done.