A Systematic Review on Explicit and Implicit Aspect Based Sentiment Analysis

Abstract

AbstractOpinion mining is also called sentiment analysis is a branch of web mining and text mining that is the process of identifying and determining the orientation of individual web users regarding various products, services, social comments on social media, different e-commerce websites, political issues, hotels, restaurants, emotions or sentiments of individual users about different entities and services of his/her interest on web or Internet. OM or SA interchangeably can be used to monitor and build a recommendation system based on individual user’s reviews that can be document-based, sentence-based, or aspect-based on reviews. Extracting features or aspects of web-based entities or services is a core task of SA. Aspects or features are broadly categorized as implicit and explicit features. The recommendation system-based build with such functionality can enable users to improve buying or selling decisions, also it can improve market intelligence, improve the manufacturing of products, improve services to users, and so on. Most of the time, reviews contain clear information (explicit), but they may also contain information that is not clearly stated or hidden (implicit) that cannot be ignored as may lead to the wrong decision or recommendation to individual users. This area has many challenging issues or problems that are still unaddressed or unsolved.KeywordsSentiment analysisOpinion miningImplicit aspectsExplicit aspectsRecommendation system