Aspect-based Opinion Mining: A Survey

Opinion mining has been an emerging research field in Computational Linguistics, Text Analysis and Natural Language Processing (NLP) in recent years. It is the computational study of people‟s opinions towards entities and their aspects. Entities usually refer to individuals, events, topics, products and organizations. Aspects are attributes or components of entities. In the last few years, social media has become an excellent source to express and share people‟s opinion on entities and their aspects. With the availability of vast opinionated web contents in the form of comments, reviews, blogs, tweets, status updates, etc. it is harder for people to analyze all opinions at a time to make good decisions. So, there is a need for effective automated systems to evaluate opinions and generate accurate results. Sentiment Analysis, Emotion Analysis, Subjectivity Detection has also become an active research area in recent years along with opinion mining. This article presents a brief overview of opinion mining and its classifications and specifically focuses on the sub topic aspect-based opinion mining, its approaches, metrics used for evaluation and latest research challenges. General Terms Opinion Mining, Text Mining.