Research on Hotel Service Quality Management Based on Data Mining of Online Reviews

The service quality of hotels is an important factor influencing customers’ hotel choices. This study takes the Grand Hyatt Guangzhou as a research case. It uses the Octopus Collector to collect online review texts from Ctrip over the past three years. Then, with the help of ROST CM6 software, it analyzes the online texts, extracts the high - frequency words in customers’ evaluations of the hotel's service quality, and classifies them into evaluation indicators. Finally, it constructs an evaluation index framework for the service quality of the hotel in this research case. The primary and secondary indicators are as follows: Core Services (service response efficiency, professional qualities of employees, additional services), Facilities and Equipment (functional facilities, maintenance status), Hygiene and Environment (air quality, cleanliness), and Experience and Perception (location convenience, comfort, cost - performance). Furthermore, it analyzes the emotional tendencies of the high - frequency words, explores the positive and negative emotional attributes of customers, and understands customers’ needs and the hotel's deficiencies. Finally, practical suggestions are put forward, with the expectation of providing reference for the management of hotel service quality.