A Thousand Words Express a Common Idea? Understanding International Tourists’ Reviews of Mt. Huangshan, China, through a Deep Learning Approach

Cheng Chai, Yao Song and Zhenzhen Qin
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Cheng Chai: School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK
Yao Song: School of Design, The Hong Kong Polytechnic University, Hong Kong 80309, China
Zhenzhen Qin: School of Journalism and Communication, Anhui Normal University, Wuhu 241002, China

Land, 2021, vol. 10, issue 6, 1-15

Abstract: 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.

Keywords: deep learning; landscape; tourist experience; landscape experience; tourist review; BERT; natural language processing (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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