Abstract
Opinion mining is becoming a popular area in today’s world but before the invention of web 2.0 people were only able to view the information but now they are also able to publish the information on Web in the form of comments and reviews. The user generated content forced organization to pay attention towards analyzing this content for better visualization of public’s opinion. Opinion mining or Sentiment analysis is an autonomous text analysis and summarization system for reviews available on Web. Opinion mining aims for distinguishing the emotions and expressions expressed within the reviews, classifying them into positive or negative and summarizing into the form that is quickly understood by users. Feature based opinion mining performs fine-grain analysis by recognizing individual features of an object upon which user has expressed his/her opinion. This paper gives an idea of various methods proposed in the area of feature based opinion mining and also discusses the limitations of existing work and future direction in feature based opinion mining.
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