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Social Media Based Behavior Prediction for Pakistan’s Peoples


Nasir Amin, Muhammad Awais, Asad Cheema, Muhammad Mohsin Ashraf, Ayesha Shahid


Vol. 18  No. 10  pp. 36-42


Behavior prediction from sentiment analysis is a field of Natural Language Processing which addresses the problem of extracting sentiment or, more generally, opinion from text. In this research paper specifically predict the behavior of the Pakistan’s peoples from tweeter datasets and sentiment polarity classification problem in Twitter aiming to classify messages based on the polarity of the sentiment towards behavior, where the tweets of behavior are extracted from twitter API. In the Methodology, implementation of machine learning models and experimental test to prove this research study. Machine learning models that are using in methodology are Random Forest Model (RFM), Decision Tree (DT) and Na?ve Bays (NB) classifier. It is also observed and compare the results as well as to improve the results by using the python that can never use before it for this research work.


Social Media, Prediction, Behavior, PTA, CSV, Machine Learning, Sentiments