Abstract: The ability to correctly identify the sentiment expressed in user-reviews about a particular product is an important task for several reasons. Product owner’s point-of-view, if there is a negative sentiment associated with a particular feature of a product, the manufacturer can take immediate action(s) to address the issue. Failing to detect a negative sentiment associated with a product from numerous user-review might result in decreased sales. User’s point-of-view, in online stores where one cannot physically touch and evaluate a product as in a real-world store, the user opinions are the only available subjective descriptors of the product and the numerous user-reviews. Correctly identifying the sentiment expressed in user-reviews will help the new users to make decision on buying. Cross Domain opinion grading is the task of adopting a sentiment classifier trained on a particular domain to a different domain by adopting previous feedbacks of a particular products. Primarily data is collected and analysed by using sentiword net. Data is fed in textual form, then it will convert to numerical form and displays in the matrix form. It assists the Product Owners and Potential buyers of a product to easily understand the overall opinion about that product and it automatically classifies the user reviews according to sentiment expressed in them. It helps Product Owner to improve their Product and increase the sale. It helps potential buyer to make right buying decision.
Keywords: Cross domain; Sentiword net; Source domain; Target domain; SPF.