Education, Science, Technology, Innovation and Life
Open Access
Sign In

A study on the recognition of Korea National Park by using social network analysis based on big data

Download as PDF

DOI: 10.23977/tmte.2021.040203 | Downloads: 20 | Views: 1007

Author(s)

Wenhui Shan 1

Affiliation(s)

1 Hotel & Tourism, Honam University, Gwangju, 62399, Republic of Korea

Corresponding Author

Wenhui Shan

ABSTRACT

The purpose of this studies to generate the tourist's perception of National Park in Korea by using social network analysis based on big data. Data were gathered from Naver, Daum, and Google as analysis of data channels. The search period was limited to three years from Jan.1, 2018, to Dec.31, 2020. a total of 30,183 text data were collected by using the Textom program, and keywords analysis and frequency analysis of the data collected through text mining was performed to identify Korea National park. Density analysis, network concentration analysis, centrality analysis, and CONCOR analysis were performed using the Ucinet 6 program. As a result, first, various keywords related to Korea National Park such as ‘National Park Service, Ministry of Environment, hiking, trail, travel, sunrise, picture, autumn, sunset, beautiful’ were extracted. Second, as a result of CONCOR analysis, finally, 4 groups were formed. Confidently, this study discussed the implications of a marketing strategy for Korea’s National Parks as a result of the semantic network analysis study. Therefore, the activation of National Park, which is a typical tourism form of sustainable tourism, is expected to be an alternative to the tourism industry in Korea.

KEYWORDS

Big data, Korea National Park, Social network analysis, Text mining

CITE THIS PAPER

Wenhui Shan. A study on the recognition of Korea National Park by using social network analysis based on big data. Tourism Management and Technology Economy (2021) 4: 14-20. DOI: http://dx.doi.org/10.23977/tmte.2021.040203.

REFERENCES

[1] Agyeman, Y. B., Aboagye, O. K., & Ashie, E. (2019). Visitor satisfaction at kakum national park in Ghana. Tourism Recreation Research, 44(2), 178-189.
[2] Böhn, D. (2021). National Parks in Germany: Let nature be nature–But which nature?. International Journal of Geoheritage and Parks, 9(1), 30-35.
[3] Ferretti-Gallon, K., Griggs, E., Shrestha, A., & Wang, G. (2021). National parks best practices: Lessons from a century's worth of national parks management. International Journal of Geoheritage and Parks.
[4] Gissibl, B.,Höhler, S., & Kupper, P. (2012). Civilizing nature: National parks in global historical perspective. New York, NY: Berghahn Books. 
[5]  Gursoy, D. & McCleary, K. W. (2004). “An integrative model of tourists' information search behavior”, Annals of tourism research, 31(2), 353-373. 
[6]  Hausmann, A., Toivonen, T., Slotow, R., Tenkanen, H., Moilanen, A., Heikinheimo, V., & Di Minin, E.(2018). Social media data can be used to understand tourists’ preferences for nature‐based experiences in protected areas. Conservation Letters, 11(1), e12343.
[7] Korea National Park Service. (2020). 2020 National Park Basic Statistics.
[8] Lee S. W. (2010). A Study on the Relation between Environmental Awareness and Behavior of National Park Tourists: With the Emphasis on Chiaksan National Park. Published masteral dissertation. Sangji University. Republic of Korea.
[9] MacKintosh, B. (1985). The National Parks: Shaping the System. Washington, D.C.: The National Parks Service.
[10] Souza, C. N., Rodrigues, A. C., Correia, R. A., Normande, I. C., Costa, H. C., Guedes-Santos, J., & Ladle, R. J. (2021). No visit, no interest: How COVID-19 has affected public interest in world's national parks. Biological Conservation, 256, 109015.

Downloads: 5269
Visits: 149929

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.