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Opinion Mining using Machine Learning Approaches: A Critical Study
J. Ramakrishnan, D. Mavaluru, K. Srinivasan, A. Mubarakali, C. Narmatha,
Published in Institute of Electrical and Electronics Engineers Inc.
With the advancement of internet technology, there is a large volume of information exists on the web for users of the internet. These users not just utilize the accessible resources on the web yet, in addition, give their feedback, consequently creating more useful data. Opinion mining (OM) is contemplated as a subfield of NLP, information retrieval, and data mining. It is the way toward extricating people's thoughts and observations from unformed content, which with respect to the development of online social media and the huge amount of user feedback, has gotten an effective, attractive and furthermore complex issue. The fundamental in OM is classifying the polarity of text as far as positive (good), neutral (surprise) or negative (bad). This paper is proposed to review the methods and applications of opinion mining. This paper presents a review of OM and related strategies and additionally discusses the applications and difficulties for OM with knowledge into previous researchers. © 2020 IEEE.