Aspect-Based Sentiment Analysis: A Survey of Deep Learning Methods

Abstract

The process of analyzing, processing, concluding, and inferring the sentiment of subjective texts is known as sentiment analysis (Shandilya et al. in Aspect-based sentiment analysis survey of deep-learning. IEEE [1]). Sentiment analysis is used by businesses to better understand their customers public opinion polling, market research, and brand evaluation reputation, comprehension of customer experiences, and social media research the media's influence. Depending on the various aspect requirements granularity is classified as positive, negative and neutral of the sentiment analysis. This article provides an overview of recently proposed methods for dealing with a sentiment analysis problem based on aspects (Liu et al. in Aspect-based sentiment analysis-a survey of deep learning methods. IEEE [2]). There are currently three popular approaches: deep learning, lexicon-based, and traditional machine learning methods.