Information Mining Based on Internet Travel Notes Text
LU Ke-bin, Y. C. Tang · 2023
This article takes the tourist attractions in Anhui Province as the research object, obtains the online travel notes of the scenic spots through web crawler technology, builds an emotional dictionary in the field of tourism based on the improved SO-PMI algorithm, and conducts sentiment analysis on the travel texts, and then uses the LDA model to extract the topics. The research shows that: (1) The emotional distribution of travel notes is as follows: 67% are positive evaluations, 12% are neutral evaluations, and 21% are negative evaluations. It can be seen that tourists' emotional tendencies towards scenic spots in Anhui Province are mainly positive. (2) The model extracts 4 positive topics: architectural style, scenic spot services, tourist experience and play items; 3 negative topics: scenic spot fees, scenic spot management and ticket prices. (3) Tourists'positive evaluation of scenic spots in Anhui Province is mainly reflected in the beautiful scenery and unique attractions, which are worthy of tourists'travel experience and recommendation; negative evaluations are mainly concentrated in the high ticket prices of scenic spots and expensive fees in scenic spots, which make some tourists I feel that the price/performance ratio of playing is not high.