Sentiment-Aware Neural Recommendation for User Experience Analysis in Short-Term Rentals: A Case Study from Chongqing

The paper examines the process of user accommodation at online travel sites by combining the ideas of sentiment analysis and neural network modeling. Using a homestay market in Chongqing as a case study, we will gather and analyze user reviews and use a field-specific sentiment lexicon to find out what emotional aspects are crucial in terms of satisfying the reservation process. Another recommendation model a matrix factorization-deep neural networks hybrid model is also developed to allow matching of user preferences with the right listings. As shown by experimental findings, this leads to improvement in accuracy of the discovery of user needs and suggestions of high-satisfaction accommodations. This study can be used to enhance the current state of personalized services and streamline the homestays experiences to suit a young traveler.