A comprehensive survey on aspect-based sentiment analysis Online publication date: Wed, 22-Dec-2021
by Kaustubh Yadav; Neeraj Kumar; Praveen Kumar Reddy Maddikunta; Thippa Reddy Gadekallu
International Journal of Engineering Systems Modelling and Simulation (IJESMS), Vol. 12, No. 4, 2021
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.
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