A Survey Paper on Twitter Sentiment Analysis of Current Affairs

Sentiment Analysis is an important type of text analysis that aims to support decision making by extracting & analyzing opinion oriented text. Indentifying positive & negative opinions & measuring how positively & negatively an entity is regarded. sentiment analysis on social media data while the use of machine learning classifier for predicting the sentiment orientation provides a useful tool for users to monitor brand or product sentiment. Document level sentiment analysis is used which consists of Term Frequency (TF) and Inverse Document Frequency (IDF) values as features along with Fuzzy Clustering which results in positive and negative sentiments. As more & more user express their views & opinion on twitter. So twitter becomes valuable sources of people’s opinions. Tweets data can be used to infer people’s opinion for marketing & social studies. Twitter sentiment analysis that can spot the general people’s opinion in regard to social event which are going to be in current on twitter. In this research will take current scenario which are going to be on twitter as an example for sentiment analysis. In these will use the proposed feature extraction model with SVM classifier. Using this can obtain greater accuracy as compared to previous research work.