Analysing the causes of tourists’ emotional experience related to tourist attractions from a binary emotions perspective utilising machine learning models

Abstract

ABSTRACT This study constructs a theoretical framework to analyse the causes of tourists' binary emotional experiences. It applies Support Vector Machine (SVM) and Latent Dirichlet allocation (LDA) machine learning models, combined with geospatial analysis methods, to online reviews of five types of tourist attractions in Dali, China. The results indicate that positive sentiments predominated across Dali Prefecture, though some attractions in Dali City received negative ratings. Furthermore, service experience and price were common influences on tourists' sentiments. This study reveals the causes of tourists' varied emotional experiences at tourist attractions from a binary emotional perspective.