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A Study on the Change of Tourism Marketing Trends through Big Data

  • Se-won Jeon (Department of Immersive Content Convergence, Graduate School, Kwangwoon University) ;
  • Gi-Hwan Ryu (Department of Tourism and Food Industry, Graduate School of Smart Convergence, Kwangwoon University)
  • Received : 2024.05.02
  • Accepted : 2024.05.16
  • Published : 2024.06.30

Abstract

Recently, there has been an increasing trend in the role of social media in tourism marketing. We analyze changes in tourism marketing trends using tourism marketing keywords through social media networks. The aim is to understand marketing trends based on the analyzed data and effectively create, maintain, and manage customers, as well as efficiently supply tourism products. Data was collected using web data from platforms such as Naver, Google, and Daum through TexTom. The data collection period was set for one year, from December 1, 2022, to December 1, 2023. The collected data, after undergoing refinement, was analyzed as keyword networks based on frequency analysis results. Network visualization and CONCOR analysis were conducted using the Ucinet program. The top words in frequency were 'tourists,' 'promotion,' 'travel,' and 'research.' Clusters were categorized into four: tourism field, tourism products, marketing, and motivation for visits. Through this, it was confirmed that tourism marketing is being conducted in various tourism sectors such as MICE, medical tourism, and conventions. Utilizing digital marketing via online platforms, tourism products are promoted to tourists, and unique tourism products are developed to increase city branding and tourism demand through integrated tourism content. We identify trends in tourism marketing, providing tourists with a positive image and contributing to the activation of local tourism.

Keywords

References

  1. Kim Kwanyong, "A Study on the Effect of Tourism Marketing Channel Characteristics, Tourism Brand Equity, and Tourist Attraction on Behavioral Intentions : Focusing on Jeollanam-do," Graduate School Kyonggi University, Ph. D. Dissertation, 2021.
  2. Park Young-kwang and Lee Seung-kon, "The Effect of Short-form Advertising on SNS Tourism Marketing Using the AISAS Model," Vol. 45, No. 9, pp. 747-760, 2023. DOI: https://doi.org/10.33645 /cnc.2023.09.45.09.747 https://doi.org/10.33645
  3. Lee Jong Hyun, "A Study on the Effects of Social Media Tourism Marketing Activity on Jeju Special Self-Governing Province Local Image and Visit Intention," Graduate School of Tourism & Hospitality Kyonggi University, MA.Thesis, 2020.
  4. Park Byeong-Hyeon, Kim Yeong-Gug and Nam Jang-Hyeon, "A Study on Zero-calorie drinks Perception with Big Data Analysis," Journal of Tourism Enhancement, pp.115-164, 2024. DOI: https://doi.org/10.35498/kotes.2024.se6.115
  5. Jiang Shan, "A Study on the Perception of K-culture of Chinese Using Big Data Analysis and Q Methodology," Dong-Eui university, a doctoral dissertation, 2024.
  6. Yang Soung-hoon, "Hallyu Tourism Discourses' Change and Future Direction: Semantic Analysis on Media and SNS Text," Journal of Tourism Enhancement, Vol. 11, No. 3, pp.1-16, 2023.
  7. Lee Yong kyu, "A study on Changes in Travel Marketing Targets Before and After COVID-19 Pandemic Using SNS Big Data," Journal of Marketing Studies, Vol. 30, No. 2, pp. 30-49, 2022. DOI: http://dx.doi.org/10.22736/jms.30.2.02
  8. Se -won Jeon, Youn Ju Ahn and Gi -Hwan Ryu, "A Study on Gamification Consumer Perception Analysis Using Big Data," International Journal of Advanced Culture Technology, Vol.11, No .3, pp. 332 -337, 2023. https://doi.org/10.17703/IJACT.2023.11.3.332
  9. MinHwan Ko and Park Yun Mi, "A study on future tourism in the post-COVID-19 era using text mining based on big data: Focused on LAN cable tours," International Journal of Tourism and Hospitality Research, Vol. 36, No. 5, pp. 79-92, 2022. DOI: https://doi.org/10.21298/IJTHR.2022.5.36.5.79
  10. Se-won Jeon, Sung-Woo Park, Youn Ju Ahn and Gi-Hwan Ryu, "A Study on User Perception of Tourism Platform Using Big Data," The International Journal of Advanced Smart Convergence, Vol. 13, No. 1, pp. 108-113, 2024. DOI: http://dx.doi.org/10.7236/IJASC.2024 .13.1.108