Mining Social Network Data for Predictive Personality Modelling by Employing Machine Learning Techniques

摘要: Facebook, Twitter, LinkedIn and Tumblr are online social networking platforms where the users send receive messages on topic of their choice express sentiments. The usage these sites has exponentially increased over last few years, thereby increasing information posted media sites. quantity information/tweets keeps a daily basis. Twitter become stable platform to identify personality-related indicators encrypted in user profiles pages related subject. In this proposed work, we present scalable real-time system for sentiment analysis data. This work will collect tweets real time thus provide basis each tweet into either positive or negative based mind-set user, providing regarding certain topic. relies feature extraction from generated time. A supervised learning approach ensemble is used train various classifiers features extracted. design implementation Flask Celery been carried out which contains classification tasks. with respect size input data rate arrival. merits terms scalability, performance accuracy was evaluated experimentally.