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http://dx.doi.org/10.14400/JDC.2021.19.8.033

Spatial analysis based on topic modeling using foreign tourist review data: Case of Daegu  

Jung, Ji-Woo (Department of Library and Information Science, Kyungpook University)
Kim, Seo-Yun (Department of Statistics, Yeungnam University)
Kim, Hyeon-Yu (Department of Computer Science, Kyungpook University)
Yoon, Ju-Hyeok (Department of Computer Science, Kyungpook University)
Jang, Won-Jun (Big Data Center, Daegu Digital Industry Promotion Agency)
Kim, Keun-Wook (Big Data Center, Daegu Digital Industry Promotion Agency)
Publication Information
Journal of Digital Convergence / v.19, no.8, 2021 , pp. 33-42 More about this Journal
Abstract
As smartphone-based tourism platforms have become active, policy establishment and service enhancement using review data are being made in various fields. In the case of the preceding studies using tourism review data, most of the studies centered on domestic tourists were conducted, and in the case of foreign tourist studies, studies were conducted only on data collected in some languages and text mining techniques. In this study, 3,515 review data written by foreigners were collected by designating the "Daegu attractions" keyword through the online review site. And LDA-based topic modeling was performed to derive tourism topics. The spatial approach through global and local spatial autocorrelation analysis for each topic can be said to be different from previous studies. As a result of the analysis, it was confirmed that there is a global spatial autocorrelation, and that tourist destinations mainly visited by foreigners are concentrated locally. In addition, hot spots have been drawn around Jung-gu in most of the topics. Based on the analysis results, it is expected to be used as a basic research for spatial analysis based on local government foreign tourism policy establishment and topic modeling. And The limitations of this study were also presented.
Keywords
Tourism Analysis; Foreign Tourists; Review Data; Topic Modeling; LDA; Spatial Autocorrelation;
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Times Cited By KSCI : 1  (Citation Analysis)
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