Abstract

Website and social networking outlets have become more and more popular places for people to voice their opinions on different issues, in particular their frustrations with brands and corporations. Similarly, emotion analysis is starting to be incorporated into corporations owing to the existence of an abundance of opinionated content from the digital channels provided by customers. The written narratives may be written in an optimistic, a negative, or a more analytical style. Travellers’ ratings are an important influence on whether the hotel is a beginning or a long-term client. It helps the hotels aware of their worth in the industry, and improves their position by helping customers better define their qualities in a competitive setting. This research’s key goal is to identify ways to improve hotel opinion analyses. Lexical-based combination and deep learning will yield the most appropriate results. Firstly, it uses predefined terms to look for polarity in the lexicon dictionary, and then employs the machine learning techniques as the final layer. The article discusses what is yet to be done and what has been done in the analysis so far.