Tourism Destination Image Perception Model Based on Clustering and PCA from the Perspective of New Media and Wireless Communication Network: A Case Study of Leshan

Abstract

The consistency of tourists' perceptions of a destination and the public's evaluation of that perception is the foundation of destination image construction. In this paper, the principal component analysis method is used to analyze the tourism competitiveness of Leshan based on the wireless communication platform, and the obtained multisource geographic data are clustered according to the theme, using LDA (latent Dirichlet allocation) document theme generation model and topic clustering technology of K-means clustering algorithm. The hot events and hot topics that tourists care about in scenic spots are quickly extracted during the time span of this study. The model shows that tourists' destination image perception is an important antecedent variable of tourists' behavior intention, and perceived value and local attachment are two important intermediary variables. As for the overall effect of tourists' behavior intention, tourists' destination image perception has the greatest effect, followed by perceived value, and local attachment is the smallest.