When a villager is a rural homestay operator: role expectation research using the machine learning model?

Abstract

ABSTRACT With the growing development of the Chinese rural tourism industry, villagers are gradually becoming involved in tourism, and the role of rural inhabitants has shifted. However, understanding tourists’ expectations of rural tourism operators remains challenging. This paper uses machine learning techniques such as LDA and SnowNLP to analyse online review data from 115 rural homestays in Hainan Province. Five topics of role expectations are identified, which can be grouped into quality expectations, image expectations, obligation expectations and attached expectations. Corresponding types of content are then mapped onto a convertible and dynamic model of residents’ role expectations, based on the concepts of ascribed status and achieved status, to discover the mechanism of role transformation of rural homestay operators. It is worth emphasising that residents’ roles are not singular in the particular spatial context of rural tourism operations. Image expectations within the achieved status can transfer from the ascribed status, while the gap between quality expectations and reality implies rural residents’ immaturity as operators. This study holds significant implications for the management and practice of rural tourism.