The relation between online social agency comments and ratings
DOI:
https://doi.org/10.54691/bcpbm.v34i.2999Keywords:
Hotel reviews; high-frequency words; TF-IDF algorithm.Abstract
With the economic development in China, the hotel industry has grown along with the tourism industry. However, with the emergence of hotels of the same type and the renewal of consumers' consumption habits, online travel agency platforms are becoming more and more valuable as a guideline for consumers. This study analyzes users’ tendency in the process of consumption experience and the relationship between review texts and ratings of two five-star hotels close to each other to address this phenomenon. This paper mainly uses the Jieba splitter and TF-IDF algorithm to analyze. Accroding to the analysis, users are more concerned about facilities, services, and hygiene, while high-frequency words are negatively correlated with ratings indicating that user reviews are mainly complaint-oriented. This paper explores the service focus of the hospitality industry in the new business model from the platform reviews and provides guidance for future five-star hotels to improve their ratings and positive reviews in a targeted manner.
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