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Cheng Chai
School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK

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Journal article
Published: 21 May 2021 in Land
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Tourists’ experiential perceptions and specific behaviors are of importance to facilitate geographers’ and planners’ understanding of landscape surroundings. In addition, the potentially significant role of online user generated content (UGC) in tourism landscape research has only received limited attention, especially in the era of artificial intelligence. The motivation of the present study is to understand international tourists’ online reviews of Mt. Huangshan in China. Through a state-of-the-art natural language processing network (BERT) analyzing posted reviews across international tourists, our results facilitate relevant landscape development and design decisions. Second, the proposed analytic method can be an exemplified model to inspire relevant landscape planners and decision-makers to conduct future researches. Through the clustering results, several key topics are revealed, including international tourists’ perceptual image of Mt. Huangshan, tour route planning, and negative experience of staying.

ACS Style

Cheng Chai; Yao Song; Zhenzhen Qin. A Thousand Words Express a Common Idea? Understanding International Tourists’ Reviews of Mt. Huangshan, China, through a Deep Learning Approach. Land 2021, 10, 549 .

AMA Style

Cheng Chai, Yao Song, Zhenzhen Qin. A Thousand Words Express a Common Idea? Understanding International Tourists’ Reviews of Mt. Huangshan, China, through a Deep Learning Approach. Land. 2021; 10 (6):549.

Chicago/Turabian Style

Cheng Chai; Yao Song; Zhenzhen Qin. 2021. "A Thousand Words Express a Common Idea? Understanding International Tourists’ Reviews of Mt. Huangshan, China, through a Deep Learning Approach." Land 10, no. 6: 549.