Chinese Text Mining Based On The Complaint Data Of Yunnan Tourism Online Website

There are usually two kinds of online comment texts:negative and positive,we call these complaints text data with negative emotions as complaint data.At present,there are few researches on tourism complaint data in the hot research field of text mining.As one of the traditional pillar industries in Yunnan,the service quality of Yunnan tourism market has attracted much public attention.In recent years,the tourism market in Yunnan has been in chaos and the negative events and the network public opinion have been continuously triggered,which has caused the overall image of Yunnan tourism to suffer repeated damage.Therefore,natural language processing and text mining based on negative public opinion data such as visitors' online complaint data,which can promote relevant government departments and scenic spots to respond and reform actively and timely to specific issues concerned by the public and consensus,so as to make positive contributions to the renovation of Yunnan's tourism market and the transformation and upgrading of tourism industry.In this paper,we use python to crawl the news data of tourism public opinion column and tourist complaint data of complaint column on Yunnan travel websites Based on the above data,from the perspective of tourists,we analyze the main complaint areas,the main complaint types and the causes of complaints in various regions.First,based on the extraction of high frequency words,the article gets the hot issues involved in the news data of tourism public opinion column.Then,based on the data of complaint areas and complaint types,the complaint types were compared and analyzed from the geographical dimension and the time dimension respectively,and the text get that the mainly complained area in Yunnan is Kunming,Lijiang and Dali,the mainly complained types of Kunming is shopping,transportation and aviation,the mainly complained types of Dali is shopping,scenic spots and traffic,the main complained types of Lijiang is scenic spots,shopping and tour guides.Finally,deep text mining is done based on the content of complaint data,the main work includes keyword extraction based on tf-idf,LDA topic modeling and analysis and association word analysis based on Word2vec of word vector analysis.Through the above basic analysis and deep excavation,the article gets the main problems of Yunnan tourism,as well as the tourism problems involved in Lijiang,Dali and Kunming which are mainly complained,and the direction of tourism reform in various regions,which provides references and suggestions for Yunnan's tourism reform.