Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

Image Perception of Guilin Tourist Destination Based on Web Text Analysis

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  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322613,
        author={Xinchen  Lu and Qiang  Zhang},
        title={Image Perception of Guilin Tourist Destination Based on Web Text Analysis},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={text analysis method; tourist destination; "cognitive-affective" model},
        doi={10.4108/eai.17-6-2022.2322613}
    }
    
  • Xinchen Lu
    Qiang Zhang
    Year: 2022
    Image Perception of Guilin Tourist Destination Based on Web Text Analysis
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322613
Xinchen Lu1, Qiang Zhang1,*
  • 1: Guilin University of Technology School
*Contact email: zhangqiang704@163.com

Abstract

With the advent of the era of big data, collecting online travel notes to establish a text database can obtain the comprehensive perception image of tourists on tourist destinations, and provide new ideas for the research on image perception of urban tourist destinations. Tourist travel texts collected from Ctrip.com and Mafengwo are used as research samples. Based on the "cognition-emotion" model of tourist destination image perception, the high-frequency feature words of Guilin image perception are extracted by text analysis method. The results show that: (1) Yangshuo, Li River, and Yulong River are the basic cognitive images of tourists for Guilin’s tourism image. (2) Tourists are highly satisfied with tourism resources and tourism activities, and the evaluation is mainly based on neutral emotions. (3) The overall image perception is a landscape tourist attraction, the overall image perception is positive, and the overall positive perception accounts for a high proportion. (4) The travel notes semantic network diagram takes Guilin as the core, and Guilin-Yangshuo, Guilin-Lijiang, and Guilin-Yulonghe are closely related relation chains in the network diagram.