Research on destination images with information containing sentiment classification driven by multi-source data

Abstract

Current tourism research is insufficient in the construction of destination images and fine-grained sentiment analysis of tourist comments. Taking Mount Emei and other scenic spots as research sites, this paper explores the construction of a multi-dimensional label system for drawing destination images with the help of big data mining and fine-grained sentiment analysis technology and conducts fine-grained sentiment analsysis on texts from different sources by using sentiment dictionary. It has certain enlightenment for tourism scenic spot managers and marketing planners with different resource endowments to carry out tourism management, accurately match user needs and improve the image of scenic spots.