Deep Learning-based Sentiment Analysis of Trip Advisor Reviews

In language processing, sentiment analysis is an essential task that involves analyzing and understanding the opinions, feelings, and emotions expressed in a text by users. In other words, it is a way of analyzing and understanding people's feelings. Since a large amount of data is generated by customers on a variety of online platforms, it has become increasingly important for businesses to analyze this data to better understand their customers' opinions and improve their products and services according to these opinions. One of the most well-known venues for opinion sharing is TripAdvisor, where customers discuss their experiences and reviews of hotels. This proposed work offers a method for the analysis of hotel reviews on TripAdvisor based on sentiment analysis using a deep learning-based approach. The study employs Bidirectional Encoder Representations from Transformers to classify the reviews by their sentiments, after learning the characteristics of the text data. Experimental results demonstrate the comparison of a few deep learning models and provide recommendation of the suitable model for customer feedback analysis. Hotels can utilize the suggested method to examine visitor comments.