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[Purpose/Significance] In order to optimize online community services, attract and encourage more people with travel intentions to use the Internet to share and obtain travel information, this paper studies the travel information needs of users in the tourism Q&A community. [Method/Process] Firstly, by using the network text mining, we selected the Q&A content about Beijing from the Tuniu Q&A platform as a corpus. Secondly, we used two different keyword extraction algorithms: TF-IDF and TextRank to extract the keywords of each text. Finally, we constructed a co-occurrence network through Gephi and use Gephi's clustering function to clarify the theme of the keywords, so as to grasp the user's travel information needs. [Results/Conclusions] The travel information needs of users in the online travel Q&A community can be roughly divided into 7 categories: accommodation information, food information, traffic information, scenic spot information, group tour information, climate information and planning suggestions. Users have different types of travel information demands which are not separate and independent from each other. There is a staggered relationship between different demands. |
