Study On Management Of Tourism Credit Based On Sentiment Analysis

With the development of information technology,"big data" has become a distinctive feature of the development of tourism.More and more tourists will share the travel experience on the Internet,resulting in tourism big data.It plays an important role in consumer's decision-making and company's promoting,which benefits the economy.However,in this process,the negative comments that lead to the crisis of tourism crisis will also spread rapidly,which will have a bad impact on the tourist destination reputation and image.Some studies have suggested that comments of tourists can reflect the real feelings of tourists' trust in tourism enterprises,not only can provide important reference for enterprises,but also provide direct clues for tourism management department management.Therefore,how to change the traditional tourism credit management process,and how to use large data technology to tap the analysis of potential value,has become important.To solve the problems,this paper puts forward the process of tourism credit management on the basis of relevant theories,and validating the feasibility and validity of the management idea through the experimental model.In the study,the experimental model combined with the current popular sentiment analysis of the machine learning and sentiment dictionary methods.This study found that online travel comment can be an important source of data for tourism management,and sentiment analysis can help to change the traditional way of tourism credit management,quickly and accurately predict the negative comments on the development trend of tourism,so as to improve the effectiveness of tourism management credit.