This study attempts to find the underlying dimensionality in online reviews of fine-dining ethnic food restaurant experiences in Hong Kong. This research adopted semantic network analysis with Clauset–Newman–Moore clustering. Consequently, diverse and specific dimensionality was explored in this research, including ambiance, service, food, drinks, desserts, view, location, occasions, reputation and price. The content of the reviews on five types of ethnic restaurants was different in some dimensions. Marketers of fine-dining ethnic restaurants can select a particular focus when they promote their restaurants, develop menu plan and train staff members. This study implies that the quality dimensions of traditional restaurants may not accurately represent the factual dimensions, thereby resulting in implications for developing a new index of restaurant quality.
- Big data
- Semantic network analysis
- Text analytics
ASJC Scopus subject areas
- Tourism, Leisure and Hospitality Management