A fine-grained sentiment analysis of online guest reviews of economy hotels in China

ABSTRACT

This study aims to investigate the experiences of Chinese economy hotel guests by applying deep learning fine-grained sentiment analysis on 363,723 Chinese-text online reviews. Findings reveal that location is the domain that most of the positive sentiments are associated, followed by facilities, service, price, image, and reservation experience. Prominent features with negative sentiments include sound insulation, air conditioning, beddings, windows, toilets, TV sets, WiFi signals, towels, elevators, hair dryers, slippers, toilet bowls, return cash, invoices. Positive and negative sentiments are compared. This research offers an alternative approach and a more comprehensive understanding of the experiences and sentiments of Chinese economy hotel guests. Theoretical contributions and practical implications regarding economy hotel management are discussed.

本研究旨在运用深度学习精细情感分析的方法，对网上的363,723条中文评论进行调查，以了解中国经济型酒店客人的体验. 研究结果显示，最受好评的是地点，其次是设施、服务、价格、形象和预订体验. 负面情绪的主要特征包括隔音、空调、床上用品、窗户、厕所、电视机、WiFi信号、毛巾、电梯、吹风机、拖鞋、抽水马桶、退换现金、发票. 比较正面情绪和负面情绪. 本研究为中国经济型酒店客人的体验和感受提供了另一种方法和更全面的理解. 讨论了经济型酒店管理的理论贡献和实践意义.

KEYWORDS:

• economy hotel
• online reviews
• guest experience
• fine-grained sentiment analysis
• deep learning
• China

Additional information

Funding

This work was supported by the National Social Science Fund of China under Grant No.17CGL065; and the Science and Technology Commission of Shanghai Municipality under Grant No. 19692106600.