Study on Online Review Based Consumer sentimental Analysis using Machine Learning Approaches

Abstract

Analysing a vast quantity of social media data, which expands itself in volume, subjectivity, and heterogeneity on a manual basis becomes more difficult as technology progresses. In real-world applications, machine learning techniques are being used to address this issue. The goal of this article is to describe research that was conducted to assess the utility, breadth, and application of machine learning algorithms for Consumer Sentiment Analysis (CSA) in online reviews. We present a thorough evaluation of the literature in order to evaluate, examine, study and understand methodologies with directions, in order to uncover research gaps, hence showing the pairing's potential reach in the future. The major purpose is to read and analyse machine learning techniques used in the hotel and tourist industry to analyse customer sentiment in online evaluations. This research is crucial for service providers since it enables them to design customer management strategies for service selection. Additionally, there is a significant influence on scholars' future study orientations.