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Title: A thousand words express a common idea? Understanding international tourists’ reviews of Mt. Huangshan, China, through a deep learning approach
Authors: Chai, C
Song, Y 
Qin, Z
Issue Date: Jun-2021
Source: Land, June 2021, v. 10, no. 6, 549
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: BERT
Deep learning
Landscape experience
Natural language processing
Tourist experience
Tourist review
Publisher: MDPI AG
Journal: Land 
EISSN: 2073-445X
DOI: 10.3390/land10060549
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://
The following publication Chai, C.; Song, Y.; Qin, Z. A Thousand Words Express a Common Idea? Understanding International Tourists’ Reviews of Mt. Huangshan, China, through a Deep Learning Approach. Land 2021, 10, 549 is available at
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