Sentiment mining of online reviews of peer-to-peer accommodations: Customer emotional heterogeneity and its influencing factors

Abstract

The polarized problem of customers' emotional experiences in peer-to-peer accommodations has been exposed and needs urgent solution. However, a research gap remains in understanding the emotional heterogeneity. Therefore, this study explores customers' emotional heterogeneity and drivers for peer-to-peer accommodations using deep learning technologies and social network analysis. The results reveal that: For common causes, the environment is a core driver of customer emotions; While services are not necessary to positive emotions. For special causes, price value and location can stimulate customers' positive emotions, while their absence cannot affect negative emotions; The absence of household amenities cannot hinder the formation of positive emotions; While booking information triggers customers' negative emotions. This study clarifies complex demands of customer emotional experiences in sharing economy and provides a multiple emotional heterogeneity perspective for mining the emotional causes of peer-to-peer accommodation customers. Furthermore, it contributes to implications for improving customer emotional experience with differentiated strategies.