Sentiment Analysis on Social Media Data
Author(s): Sheeba Patel, Pranjali Patil, Snehal Prabhakar Patil, Swati Thorat
Publication #: IJIRCT1601031
Date of Publication: 05.04.2017
Country: India
Pages: 179-181
Published In: Volume 2 Issue 5 April-2017
Abstract
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.
Keywords: Machine Learning, Sentiment Analysis, Twitter
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