Tourism Evaluation And Analysis Of Linjiang Based On Text Mining

As a representative tourism city in Yunnan Province,Lijiang City in Yunnan Province has realized the organic integration of tourism and culture,and the growth rate of cultural industry has ranked first in Yunnan Province for 11 consecutive years.Therefore,under the background of the network economy era,how to understand the content concerned by tourists through online comment text data,promote and improve the construction and service of scenic spots,and enhance the tourist experience is of great significance.Based on this,this paper studies a large number of domestic and foreign references,based on text mining technology,takes Lijiang scenic spot as the research object from the two aspects of emotional tendency analysis and theme model,and takes the network evaluation text data published by tourists to Lijiang,Yunnan on Ctrip as the research sample,Using text mining modeling analysis,we can get the tourists’ emotional tendency judgment of Lijiang tourism and Lijiang tourism keywords,and give relevant suggestions for Lijiang tourism related departments for reference.Enterprises and local governments can use the useful information in tourists’ online comments to promote and improve the construction and service of scenic spots,and formulate accurate marketing service strategies accordingly;The tourists who are choosing the travel location or scenic spot service can also quickly understand the main characteristics of scenic spots or services according to the previous tourist experience,so as to provide some reference for their own choice decision-making.Firstly,this paper uses Octopus collector to obtain some comment text data from 2017 to 2021 in Lijiang City,Yunnan Province,and cleans and preprocesses the data,and makes descriptive analysis on the data.Then,the R software is used to segment the data,and the word frequency statistics and word cloud visualization are carried out for the word segmentation results.Then,in order to understand the correlation between words,the correlation measurement of words is carried out and the semantic network analysis is carried out by using Rost CM6.For more intuitive and quick comment content understanding of the content information,in this paper,we introduce the topic word extraction and comment topic classification using the LDA topic model based on GBS sampling.Then,in order to identify the wrong emotional tendency tag comments,this paper uses emotional tendency analysis based on emotional dictionary to realize the emotional classification of comment text data.Then combine the emotional tendency analysis with the theme model,analyze the theme model of the evaluation of different categories in the emotional tendency analysis results,and dig out the real feelings of tourists on the service characteristics in the scenic spot under different emotional tendencies.Finally,according to the survey results,some reference suggestions for potential tourists,tourist attractions and related tourist sites are provided.