ABSTRACT
Opinions play a crucial role in the decision making process. Analysis in the field of making decisions and setting policies has shown that sentiment analysis and Opinion mining has become increasingly important in the field of Information Retrieval and Web analysis. In the past years, the growth of user generated data in web forums, social networking sites and other social platforms is tremendous, which diverts our study towards mining the opinions on web. In this paper, we have presented a novel methodology to classify the tweets and the complete opinion mining system is explained on the basis of survey and analysis. A flowchart has been proposed in which the overall picture of classification of twitter data has been proposed and accuracy of the evaluation strategies by various supervised learning algorithms has been evaluated. Review data is collected for various product domains from micro blogging sites like twitter, face book.
Keywords
Opinions, Web mining, Sentiment Analysis, Supervised Learning, Mining.
1. INTRODUCTION
In recent years, we have witnessed that a huge amount of opinionated text is available which have greatly influenced our social and political systems. Twitter messages posted online is about 250 millions per day which forces the organizations to observe their status and brands by extracting and analyzing the sentiments of the tweets shared online. To keep track of products and brands on the basis of their positive or negative views can be done
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