Satisfaction of customers in Airbnb: a cross-culture text mining of online reviews

Diverse cultural values significantly influence consumer preferences and need for accommodations. Understanding these differences is crucial for managing satisfaction in peer-to-peer (P2P) settings. This study examines the differences and similarities in experience attributes reflected in consumer reviews across various languages. Employing Word Co-occurrence Networks, Factor Analysis, and Linear Regression, this study scrutinizes 243,215 Airbnb review texts in Chinese, Japanese, Korean, and English. Findings emphasize the significance of specific attributes in reviews across these languages, including convenience, location, Indoor facilities and service quality. However, the attributes affecting satisfaction show significant variations based on cultural and linguistic contexts, emphasizing the necessity for culturally sensitive business strategies.