BibTeX:

@article{IJIRSTV3I10001,
     title={Sentiment Analysis of Twitter Data using Machine Learning Approaches},
     author={Ankit Pradeep Patel, Ankit Vithalbhai Patel, Sanjaykumar Ghanshyambhai Butani and Prashant Sawant},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={10},
     pages={19--21},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I10001.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

In today’s world, micro-blogging sites has become a platform for individuals or organizations across the world to express their opinions, sentiment and experience in the form of tweets, status updates, blog posts, etc. This platform has no political and economic restrictions. This paper discusses an approach where a published stream of tweets on electronic products from the twitter micro-blogging site are then subjected to preprocessing and classified based on their emotional content as positive, negative and neutral. The performance of the unsupervised algorithm is then analyzed. The paper concludes with the comparison of the existing system with the proposed systems and applications of the research.

Classification, Data Preprocessing, Machine Learning, Sentiment Analysis