Sentiment Analysis on Social Media Data
Sheeba Patel, Pranjali Patil, Snehal Prabhakar Patil, Swati Thorat
As increasing demand of social networking sites brought a new way of expressing individuals opinion. Social networking sites have huge amount of information. The information can be seen by other user and helps to take the decision. The sentiment analysis is done by collecting the reviews of customer which are in the form of tweets. The tweets opinions are unstructured and either positive, negative or somewhat in between the two. The previous approaches used unsupervised approaches. The unsupervised approach do not contain category and there is no accurate result. The proposed approach used supervised approach. The supervised approach, Navie Bayes machine learning algorithms used label datasets for the analysis. It automatically classifies the tweets taken from social networking sites and analyze them. Its main advantage is performance i.e. precision, accuracy will increase.
Machine Learning, Sentiment Analysis, Twitter
Sentiment Analysis on Social Media Data. Sheeba Patel, Pranjali Patil, Snehal Prabhakar Patil, Swati Thorat. 2017. IJIRCT, Volume 2, Issue 5. Pages 179-181. https://www.ijirct.org/viewPaper.php?paperId=IJIRCT1601031