Aspect-based sentiment analysis: approaches, applications, challenges and trends

Abstract

Sentiment analysis (SA) is a technique that employs natural language processing to determine the function of mining methodically, extract, analyse and comprehend people’s thoughts, feelings, personal opinions and perceptions as well as their reactions and attitude regarding various subjects such as topics, commodities and various other products and services. However, it only reveals the overall sentiment. Unlike SA, the aspect-based sentiment analysis (ABSA) study categorizes a text into distinct components and determines the appropriate sentiment, which is more reliable in its predictions. Hence, ABSA is essential to study and break down texts into various service elements. It then assigns the appropriate sentiment polarity (positive, negative or neutral) for every aspect. In this paper, the main task is to critically review the research outcomes to look at the various techniques, methods and features used for ABSA. After giving brief introduction of SA in order to establish a clear relationship between SA and ABSA, we focussed on approaches, applications, challenges and trends in ABSA research.