DOI QR코드

DOI QR Code

Changes and Applications of Rural Tourism in the Post-COVID-19 Era through Social Data Analysis

소셜데이터 분석을 통한 포스트 코로나 시대 농촌관광의 변화와 적용방안

  • Kim, Young-Jin (Interdisciplinary Program in Landscape Architecture, Seoul National University) ;
  • Lee, Sung-hee (Interdisciplinary Program in Landscape Architecture, Seoul National University) ;
  • Son, Yong-hoon (Graduate school of Environmental Studies, Seoul National University)
  • 김용진 (서울대학교 협동과정 조경학) ;
  • 이성희 (서울대학교 협동과정 조경학) ;
  • 손용훈 (서울대학교 환경대학원 환경조경학과)
  • Received : 2021.09.23
  • Accepted : 2021.11.25
  • Published : 2021.11.30

Abstract

This study analysed changes in rural tourism between before and after COVID-19 using LDA topic analysis. In order to understand the changes in rural tourism, blog data including the keyword 'Gochang-gun travel' was used. As a result of LDA topic analysis with blog data retrieved, the study found nine topics in 2019 and 2020. 2019 and 2020 are, generally, consistent in topics, but the three topics related to rural experiential tourism that appeared in 2019 did not appear in 2020. In 2020, three new topics emerged: Beach vacations and campings. New travel activities of noncontact with other people(Untact tourism in Korean context) in the COVID-19 era, and The negative impacts on travel businesses and behaviours from COVID-19. Especially, the adverse effects of COVID-19 have made an enormous decline in rural experience tourism destinations and cancellation of local festivals. On the other hand, new tourism activities have emerged due to COVID-19. Those activities have included camping, drive-thru destinations, and cycling. Ecological and natural tourist sites such as Ungok Wetland, Seonunsan Mountain, Seonunsa Temple, and Gusipo Beach appeared. These tourist destinations have a quiet atmosphere and less density place noncontacting with other people when visiting. Also, because overseas travel has become difficult, long-term stay travel in rural areas has appeared. This study indicates that COVID-19 has less impacted rural tourism than other tourism destinations with these positive and negative impacts.

Keywords

References

  1. An, P., S. Eom, S. Cho & S. Kim (2020). A Study on the Creation Rural Experience Village Reflecting the Travel trends of the Post-Corona: A Case of Wi-bong Village in Jeollabuk-do, KSRP, 26(4), 27-39.
  2. Asuncion, A., M. Welling , P. Smyth & Y. W. Teh (2009). On smoothing and inference for topic models. In Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, AUAI Press. 27-34.
  3. Battisti, F. D., A. Ferrara & S. Salini (2015). A decade of research in statistics: a topic model approach. Scientometrics, 103, 413-433. https://doi.org/10.1007/s11192-015-1554-1
  4. Blei, D. & M. Jordan (2003). Modeling annotated data, In Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, 127-134.
  5. Blei, D.(2011). Introduction to probabilistic topic models. Communications of the ACM, 77-84.
  6. Blei, D (2012). Probabilistic Topic Models. Communication of the ACM, 55(4), 77-84. https://doi.org/10.1145/2133806.2133826
  7. Brauer, R. & M. Dymitrow (2014). Quality of Life in Rural Areas: A Topic for the Rural Development Policy? Bulletin of Geography. Socio-economic Series, 25, 25-54. https://doi.org/10.2478/bog-2014-0028
  8. Buehler, R. & J. Pucher (2021). COVID-19 Impacts on Cycling, 2019-2020. Transport Reviews, 41(4), 393-400. https://doi.org/10.1080/01441647.2021.1914900
  9. Chandra, Y., L. C. Jiang & C. Wang (2016). Mining social entrepreneurship strategies using topic modeling. PLoS ONE, 11(3), 1-28.
  10. Correa-Martinez, C. L., S. Kampmeier, P. Kumpers, V. Schwierzeck, M. Hennies, W. Hafezi, J. Kuhn, H. Pavenstadt, S. Ludwig & A. Mellmann (2020). A Pandemic in Times of Global Tourism: Superspreading and Exportation of COVID-19 Cases from a Ski Area in Austria. Journal of Clinical Microbiology, 58(6), 1-3.
  11. Craig, C. A (2020). Camping, Glamping, and Coronavirus in the United States. Annals of Tourism Research.
  12. Craig, C. A., & I. Karabas (2021). Clamping after the Coronavirus Pandemic. Tourism and hospitality Research.
  13. Dinarto, D., A. Wanto & L. Sebastian (2020). Global health Security COVID-19: Impact on Bintan's Tourism Sector, RSIS Commentaries, 33.
  14. Ding, W., & C. Chen (2014). Dynamic topic detection and tracking: A comparison of HDP, C-word, and cocitation methods. Journal of the Association for Information Science and Technology, 65(10), 2084-2097. https://doi.org/10.1002/asi.23134
  15. EPIS (2020). Data Story of Agriculture and Food.
  16. Galvani, A., A. Lew & M. Perez (2020). COVID-19 is Expanding Global Consciousness and the Sustainability of Travel and Tourism, Tourism Geographis, 22(3), 567-576. https://doi.org/10.1080/14616688.2020.1760924
  17. Gossling, S., D. Scott & M. Hall (2020). Pandemics, Tourism and Global Change: A Rapid Assessment of COVID-19, Journal of Sustainable Tourism, 29(1), 1-20. https://doi.org/10.1080/09669582.2020.1758708
  18. Griffiths, T. L & M. Steyvers (2004). Finding scientific topics. Proceedings of the National academy of Sciences, 101(1), 5228-5235. https://doi.org/10.1073/pnas.0307752101
  19. Guo, L., C. J. Vargo, Z. Pan, W. Ding & P. Ishwar (2016). Big Social Data Analytics in Journalism and Mass Communication: Comparing Dictionary-based Text Analysis and Unsupervised Topic Modeling, Journalism & Mass Communication Quarterly, 93(2), 232-359.
  20. Hannigan, T (2015). Close Encounters of the Conceptual Kink: Disambiuating Social Structure from Text, Big Data & Society, 2(2), 1-6. https://doi.org/10.1177/2053951715608655
  21. Karl, A., J. Wisnowski & W. H. Rushing (2015). A Practical Guide to Text Mining with Topic Extraction. Wiley Interdisciplinary Reviews: Computational Statistics, 7(5), 326-340. https://doi.org/10.1002/wics.1361
  22. Karl, M., B. Muskat & B. Ritchie (2020). Which Travel Risks are More Salient for Destination Choice? An Examination of the Tourist's Decision-making Process, Journal of Destination Marketing & Management, 18, 100487. https://doi.org/10.1016/j.jdmm.2020.100487
  23. KCTI (2020). Impact of COVID-19 on Tourism Industry and Policy Responses.
  24. Kim, Y. & Y. Son (2018). Features of the Rural Revitalization Projects in Jang-su County Using LDA Topic Analysis of Nes Data: Focused on Keyword of Tourism and Livelihood, KSRP, 24(4), 69-80.
  25. Kim, S., Y. Choi & H. Yoon (2019). The Analysis of the Visitors' Experiences in Yeonnam-dong before and after the Gyeongui Line Park Project: A Text Mining Approach. KILA, 47(4), 33-49.
  26. Kim, Y., G. Son, D. Lee & Y. Son (2021). Rural Tourism Image and Major Activity Space in Gochang County Shown in Social Data: Focusing on the Keyword 'Gochang-gun Travel', KSRP, 27(3), 103-116.
  27. KTO (2020). The Era of Untact and Changing Travel Seen through Big Data, 2020 KTO Report.
  28. Lee, S. & Y. Son (2018). Identifying Landscape Perceptions of Visitors' to the Taean Coast National Park Using Social Media Data: Focused on Kkotji Beach, Sinduri Coastal Sand Dune, and Manlipo Beach, KILA, 46(5), 10-21.
  29. Lee, C (2020). Rural Residential Environment: Identifying Trends through Text Network Analysis, KSRP, 26(1), 39-49.
  30. Lee, S. (2021). The Effect of Perceived Safety of the Travel Bubble on Image and Trust of Tourist Destination, and Safe Tourism Behavior Intension in With-Corona Era, Journal of Tourism and Leisure Research, 33(4), 99-118. https://doi.org/10.31336/JTLR.2021.4.33.4.99
  31. Lee, Y. & H. Yang (2021). COVID-19 era, Status Change of Gangwon East Coast Tourism: Tourist Road Development, Korean Society of Transportation, 18(1), 97-104.
  32. Lucas, C., R. A. Nielsen, M. E. Roberts, B. M. Stewart, A. Storer & D. Tingley (2015). Computer-assisted Text Analysis for Comparative Politics, Political Analysis, 23(2), 254-277. https://doi.org/10.1093/pan/mpu019
  33. Matthies, B. & A. Corners (2015). Computer-aided text analysis of corporate disclosures-demonstration and evaluation of two approaches, The International Journal of Digital Accounting Research, 15, 69-98. https://doi.org/10.4192/1577-8517-v15_3
  34. Moreno, A. & T. Redondo (2015). Text Analytics: the Convergence of Big Data and Artificial intelligence, International Journal of Interactive multimedia and Artificial Intelligence, 3(6), 57-64. https://doi.org/10.9781/ijimai.2016.369
  35. National Parks Service(NPS) (2021). Social Science. https://www.nps.gov/subjects/socialscience/index.htm.
  36. Seo, H. (2021). A Study on Tourism Security: Focused on Changes of Outbound Travel after Covid-19 in Korea, Journal of Tourism and Leisure Research, 33(1), 103-115. https://doi.org/10.31336/JTLR.2021.1.33.1.103
  37. Silva, L. (2021). The impact of the COVID-19 pandemic on rural tourism: a case study from Portugal. Anatolia, 1-3.
  38. Son, Y & Y. Kim (2019). The Image of Ruralism in Korea through a Text Mining for Online News Media Analysis, KSRP, 25(4), 13-26.
  39. Steyvers, M & T. Griffths (2007). Probabilistic topic models. In Handbook of latent semantic analysis (pp.439-460). Psychology Press.
  40. Vaishar, A., & M. Stastna (2020). Impact of the COVID-19 pandemic on rural tourism in Czechia Preliminary considerations. Current Issues in Tourism, 1-5.
  41. Wiedmann, G (2013). Opening up to Big Data: Computer-assisted analysis of textual data in social science. Forum Qualitative Social Research, 14(2), Art. 13.
  42. Yang, Y., H. Zhang & X. Chen (2020). Coronavirus Pandemic and Tourism: Dynamic Stochastic General Equilibrium Modeling of Infectious Disease Outbreak, Annals of Tourism Research, 83, 102913. https://doi.org/10.1016/j.annals.2020.102913