Knowledge Based Approach for Concept Level Sentiment Analysis for Online Reviews

Abstract An Evolution of internet application and usage, World Wide Web (WWW) offers a great contribution to the global society. One of the major application domains is sharing of the knowledge of users’ through a large repository of valuable opinions in the form of texts from different people on numerous products and services at the WWW. It is not a straight forward process to access these opinions because the available number is vast, and understanding what is actually meant has always been problematic considering the complexity of human languages. The main objective of the study is to provide accurate, clear cut information with a numerical justification quantifier for decision making activities based on a vast number of review comments when users are buying a product or obtaining service via WWW. This study simulates the cognitive ability of the human brain, up to some extent by identifying concepts and process with the aid of a large semantic knowledge-base that we create through natural language processing techniques. In this study, concept extraction from natural language text is achieved in two steps, part-of-speech based extraction and dependency based extraction. The experiment shows promising state of the art results, proving we have achieved successfully using human knowledge with the domain knowledge to analyze sentiments.