Merchants selling products on the Web often ask their customers to review the products that they have purchased and the associated services. As e - commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. For a popular product, the number of reviews can be in hundreds or even thousands. This makes it difficult for a potential customer to read them to make an informed decision on whether to purchase the product. It also makes it difficult for the manufacturer of the product to keep track and to manage customer opinions. As the numbers of customers are growin g, reviews received by products are also growing in large amount. Thus, mining opinions from product reviews is an important research topic. In the fast decade considerable research has been done i n academia. However, existing research is more focused towa rds categorization and summary of such online opinions. In this paper we survey various techniques to classify opinion as positive or negative and also detection of reviews as spam or non - spam
