Evaluating Opinion Strength Using Rule-Based and Fuzzy Measure Approach

Abstract

-Recently opinion Analysis gives extensive contribution of Natural Language Processing (NLP) which promises with the computational measures of opinion, subjectivity and objectivity in the given sentimental text. Opinion analysis is the mechanism of extracting meaningful knowledge from the people's review opinions, appraisals and emotions toward specific entities, events and their respective attributes. Many times these opinions drastically make impact on consumers to choose their products and entities. Some users watch movies according to rating given by bunch of peoples. Thus, it is desired to develop an efficient and effective sentiment analysis system for product buyer and for movie reviewers based on bunch of people comments regarding that particular product or movie. Here we consider the positive, negative, neutral sentences along with some special sentences in which negations words occur or a sentence containing not only but also like structural composition in the sentences which change the meaning of total sentence. We found SentiWordNet dictionary to assigns sentiment scores to each sentiment word found in comments. Sentiment words are assigned three sentiment scores: Positivity, Negativity and Objectivity with a word which lies in between the range 0 to 1. The final opinion review prediction uses Rule-Based and Fuzzy measures approach and gives the final output.