Machine Learning-Based Sentiment Analysis of Twitter Data

In these recent days, evaluation and review marks a most important role in achieving the name for a brand or an item and its administration. The basic idea behind this assessment and audit is to make the brands to be familiar with customers which empower the variety of utilization. Twitter data is used for testing the above scenario due its ample size and scattered behavior. This paper performs the hypothesis investigation about the individual's feelings depending on the collected data. The motive behind the proposed work is to assess many individual's positive view and negative view based on the content audit using the surveys from the twitter. The twitter data is estimated by applying different weighting schemes to improve the classifier accuracy.