Sentimental analysis of demonetization in india using machine learning algorithms

This paper analyzes demonetization that took place in India on 9 Nov 2016-30 Dec 2016 by honorable prime minister Narendra Modi So now we are presenting in public domain the Results From India's Demonetization Campaign using tweets posted on Twitter from 9 Nov 2016 – 30 Dec 2016. Twitter is a social network where users post their feelings, opinions and sentiments for any event. This paper transforms the unstructured tweets into structured information using open source libraries. Further objective is to build a model using Bayesian Network classification on unseen tweets on the same context. This paper collects tweets on this event under seven hashtags. This study explores three freely available resources / Application Programming Interfaces Python (APIs) for labeling of tweets for academic research. This paper proposes three sentiment prediction models using the sentiment predictions provided by three APIs. BN classifier is used to models. The performances of these models are evaluated through standard evaluation metrics. The experimental results reveal that the TextBlob API and proposed Preference Model outperformed than the other four sentiment prediction models.