Opinion mining of movie reviews at document level
This work addresses opinion mining for movie reviews, but it appears incremental as it applies a document-based classification approach without major innovations.
The authors tackled the problem of classifying movie reviews as positive, negative, or neutral at the document level, including handling negation, and reported experimental results showing the system's effectiveness.
The whole world is changed rapidly and using the current technologies Internet becomes an essential need for everyone. Web is used in every field. Most of the people use web for a common purpose like online shopping, chatting etc. During an online shopping large number of reviews/opinions are given by the users that reflect whether the product is good or bad. These reviews need to be explored, analyse and organized for better decision making. Opinion Mining is a natural language processing task that deals with finding orientation of opinion in a piece of text with respect to a topic. In this paper a document based opinion mining system is proposed that classify the documents as positive, negative and neutral. Negation is also handled in the proposed system. Experimental results using reviews of movies show the effectiveness of the system.