Hotel Ratings, Reviews, and Reply Text Dataset

In recent years, with the rapid development of the tourism and online booking markets, customer reviews and feedback received by hotels have become increasingly important. However, the unstructured nature of this text data poses challenges for data analysis and customer service. Current solutions mainly rely on manual analysis or simple sentiment analysis models, making it difficult to handle large volumes of data and thoroughly understand customer needs. This dataset addresses the automation and intelligent analysis needs of the hotel industry by providing a set of high-quality rating, review, and reply text data to enhance the accuracy of conversation analysis and sentiment judgment. The text data in this dataset were obtained by collecting public review and reply data from online travel platforms, and the collection process strictly adhered to privacy protection and data compliance requirements. In terms of quality control, the data underwent multiple rounds of annotation and consistency checks, and were reviewed by a team of linguistic experts and industry consultants to ensure consistency and accuracy of the annotations. The annotation team consists of 20 individuals with a linguistic background and extensive experience in text data processing. Data preprocessing includes steps such as denoising, word segmentation, and sentiment annotation, using the latest NLP technology tools. Data storage uses JSON format, which is clearly structured, easy to integrate and extend.