Abstract: Now-a-days due to the rapid growth of internet, people are expressing their views and opinions regarding, products, services and policies on the web in large numbers. This huge amount of feedback is very crucial for both organizations as well as individuals. The task of analysing these reviews is done by Opinion Mining (also known as Semantic Analysis). It aims for distinguishing the emotions expressed within the reviews, classifying them into positive or negative opinions and summarizing it into a form that is easily understood by users. Opinion Mining can be used by organizations to help improve their products and services. Also, it can be used by individuals in the process of decision making. This paper presents a review that covers the different techniques and approaches that are used in opinion mining systems. Also, this paper highlights various application areas and challenges related to the Opinion Mining.
Keywords: Opinion Mining, Sentiment Analysis, Supervised Learning, Unsupervised Learning, Semi-Supervised Learning, Challenges, Application Areas.