Deep Sentiment Analysis of the Feelings Expressed by Tourists Based on BERT Model

In response to the call to consolidate and expand the success of poverty alleviation and promote the overall revitalization of the countryside, rural tourism is taken as the research direction in this paper. In the existing research work on rural areas of tourism to poverty alleviation, it is mainly to put forward feasible suggestions for the overall level or to carry out one-way developing analysis for individual areas. A personalized analysis of rural areas of tourism to poverty alleviation from the perspective of users with real travel experience is conducted innovatively in this paper, which can enrich the research content of travel behavior. Through the research, training, and application of the Bidirectional Encoder Representation from Transformer (BERT) model, a deep sentiment analysis of the feelings expressed by tourists in demonstrative areas of tourism to poverty alleviation in China via Trip.com is conducted in this paper. The experiment shows that the accuracy of the BERT model on the test set is 86.9%. Based on completing the sentiment classification, this experiment completed the drawing of the word cloud by counting the frequency of sentiment words in the comments of different tendencies and completed the related results display on the WeChat Mini Program. Tourists can access the platform to learn about the scenic features, geographical location, cultural background, advantages, disadvantages, and characteristics of the scenic spot in advance.