A comprehensive survey on aspect-based sentiment analysis. (17th December 2021)

• Record Type: Journal Article
• Authors: Yadav, Kaustubh; Kumar, Neeraj; Maddikunta, Praveen Kumar Reddy; Gadekallu, Thippa Reddy
• Is Part Of: International journal of engineering systems modelling and simulation. Volume 12:Number 4(2021)
• Page Start: 279
• Page End: 290
• Publication Date: 2021-12-17
• Subjects: aspect-based sentiment analysis? ABSA? neural networks? rule-based approach? machine learning? naive Bayes; Engineering systems -- Computer simulation -- Periodicals; Engineering systems -- Mathematical models -- Periodicals; 620.0042
• Languages: English
• ISSNs: 1755-9758

Abstract

Aspect-based sentiment analysis (ABSA) is the sub-field of natural language processing that deals with breaking or splitting texts into aspects and then classification into sentiments like happy, sad, angry, etc. towards the aspect. Aspect-based sentiment analysis provides more information about the context than general sentiment analysis. In this survey paper, we compared a variety of papers and the methods that were introduced through them on achieving better results for the problem at hand. As ABSA is currently being used for customer satisfaction and product feedback most of the papers have datasets containing reviews. This survey paper discusses various solutions in-depth and gives a comparison between them. Firstly, we discuss rule-based approaches and then move to complex approaches that involve both rule-based approaches and neural networks. Also, major emphasis is shed on the principles and the workflow of the method discussed.