Research On Satisfaction Of Homestay Based On Text Mining

With the vigorous development of China's tourism industry,the residential care industry has been expanding rapidly in the past ten years.The number of residential care homes has been increasing.On the one hand,it has brought operating pressure to residential care homes.On the other hand,it has also made it more difficult to evaluate the satisfaction of residential care homes.The popularity of the Internet and mobile Internet has led to an explosion in the number of online reviews.The proposal of the big data era has enabled enterprises to focus on objective data,which can more scientifically and truly reflect the satisfaction of residential care homes and provide important basis and guidance for the decision-making of residential care home management.After investigation,we found that the current research on the satisfaction degree of residential accommodation has established a certain foundation,but the number of researches on residential accommodation nationwide is very small.In addition,most of the methods used in the research on the satisfaction degree of residential homes are also focused on the questionnaire survey method,and there are still a few methods that use text mining technology to intuitively feel the attitudes of residential home consumers.To sum up,this paper makes full use of the comment information on the online comment website,combines it with the satisfaction evaluation of the residential quarters,and studies the satisfaction of the residential quarters by using the method of text mining.The main research work and relevant conclusions are as follows:First,the crawling rules and routes are defined for the comments of Ctrip netizens by using the web crawler technology of Gooseeker software,and the sample data are crawled.Secondly,visual analysis and LDA thematic model analysis are carried out on the sample data obtained above,mainly using R language software and ROST CM software.Among them,visual analysis mainly starts from two aspects of word cloud picture and semantic network,and obtains several aspects that consumers pay most attention to,namely "service","room" and "environment".Based on the characteristics analysis of LDA theme model analysis,the first 8subject headings are summarized.Through the quarterly LDA theme model analysis results,the change of theme with time can be seen.Third,the analysis of home stay satisfaction is based on the emotional dictionary to analyze the content of the reviews.Python software is used to calculate the emotional value of each review data,and the degree of home stay satisfaction is defined by the positive and negative and absolute values of the emotional value.Descriptive analysis shows that positive emotions account for 70.6% and negative emotions account for 19.8%.Among the positive emotion scores,scores of 10 to 20 account for the most,while negative emotion scores of-10 to0 account for the most.Fourth,using hierarchical clustering method to study the influencing factors of residential accommodation,five categories are obtained,namely,guest room hardware,overall service,catering,geographical location and cost performance.The emotional tendency of each influencing factor is calculated,and the correlation between the five categories and emotional tendency is analyzed by using the contingency table.Through the research,we found that the overall service satisfaction was the highest,reaching 82.7%,which showed that the residential accommodation basically performed well in service.The most negative negative is the guest room hardware,accounting for 33.6%,and the negative negative performance of catering is also relatively strong,accounting for 27.2%,which shows that consumers are less satisfied with the guest room hardware facilities and catering.At the same time,a contingency table is used to analyze the correlation between different regions and seasons and emotional tendencies,and a conclusion is reached that the northeast region has the highest degree of satisfaction with residential accommodation and the summer has a higher degree of satisfaction with residential accommodation.Finally,combining theory with practice,this paper puts forward suggestions to improve customer satisfaction from six aspects: strengthening hardware equipment,improving the overall service level,improving the catering level,weakening the impact of light and busy seasons,attaching importance to big data marketing and strengthening the rendering of regional folk culture.