The relation between online social agency comments and ratings

With the economic development in China, hotel industry has grown along with tourism industry. However, emergence of hotels same type and renewal consumers' consumption habits, online travel agency platforms are becoming more valuable as a guideline for consumers. This study analyzes users’ tendency process experience relationship between review texts ratings two five-star close to each other address this phenomenon. paper mainly uses Jieba splitter TF-IDF algorithm analyze. Accroding analysis, users concerned about facilities, services, hygiene, while high-frequency words negatively correlated indicating that user reviews complaint-oriented. explores service focus hospitality new business model from platform provides guidance future improve their positive targeted manner.