Domain Independent Feature Extraction using Rule Based Approach

Abstract

Sentiment analysis is one of the most popular information extraction tasks both from business and research prospective. From the standpoint of research, sentiment analysis relies on the methods developed for natural language processing and information extraction. One of the key aspects of it is the opinion word lexicon. Product's feature from online reviews is an important and challenging task in opinion mining. Opinion Mining or Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the user's views or opinions. In this paper, we developed an approach to extract domain independent product features and opinions without using training examples i.e, lexicon-based approach. Noun phrases are extracted using not only dependency rules but also textblob noun phrase extraction tool. Dependency rules are predefined according to dependency patterns of words in the sentences. StandfordCoreNlp Dependency parser is used to identify the relations between words. The orientation of words is classified by using lexicon-based approach. According to the experimental results the system gets good performance in six different domains.