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.
| Original language | English |
|---|---|
| Pages (from-to) | 71-95 |
| Number of pages | 25 |
| Journal | Journal of Hospitality Marketing and Management |
| Volume | 30 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2021 |
Keywords
- China
- deep learning
- economy hotel
- fine-grained sentiment analysis
- guest experience
- online reviews
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