📝 Classifying Personality Of A Person Based On His Twitter Data

A Natural Language Processing (NLP), Machine Learning and Data Mining project, which will automate the screening process before hiring a professional or can be used in psychiatry to check effectivity of patient therapy.

● Uses the Twitter REST API to mine tweets for personality identification.
● Create n-grams and word vectors for the hashtags, emoticons and phrases using NLP techniques like TF-IDF.
● Train the machine to classify the personality types by using a Naive-Bayes Text Classifier.
● Accurately predict the user’s Myers-Briggs personality type using 10-fold cross validation.

🌈 Types of Personalities :

In Myer's Briggs Type indicator Classification we have 16 types of personality which can be categorized as :

🚀 Usage :

1. First step is to run the requirement.txt file to install all the libraries and dependencies.
2. Run pyGen.py first to generate your naive bayes classifier models for all 4 different classes. It will generate few scores which will give the training data size and the features used while training the model.
3. Run pyPredict(use your own Twitter keys) and enter the username you want to predict.

🌴 Contribution :

// yet to be added //