Predicting Customer Sentiment with Vietnamese Hotel Services by LSTM Model

Abstract

The development of e-commerce has led to the strong growth of an electronic hotel booking platform. Big data analytics in the hospitality industry offers hotel managers and travelers many benefits. This study aims to predict the sentiment of customers based on data from the TripAdvisor website to understand customers' attitudes toward hotel services in Vietnam. Review data of customers is collected from TripAdvisor with 22, 287 reviews of 12 hotels in 06 major cities in Vietnam. An LSTM model is applied to train and predict customers' sentiments. The results of this study with an accuracy of 96% show the appropriateness of this model for predicting customer attitudes and satisfaction toward hotel services in Vietnam.