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A Social Network Analysis of Tourist Movement Patterns in Blogs: Korean Backpackers in Europe

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  • Hee Chung Chung

    (Department of Hotel Management, College of Hotel and Tourism Management, Kyung Hee University, Seoul 02447, Korea)

  • Namho Chung

    (Department of Hotel Management, College of Hotel and Tourism Management, Kyung Hee University, Seoul 02447, Korea)

  • Yoonjae Nam

    (Department of Culture, Tourism & Contents, College of Hotel and Tourism Management, Kyung Hee University, Seoul 02447, Korea)

Abstract

Given recent developments in information and communication technology, the number of individual tourists enjoying free travel without the advice of travel agencies is increasing. Therefore, such tourists can visit more tourist destinations and create more complex movement patterns than mass tourists. These tourist movement patterns are a key factor in understanding tourist behavior and they contain various information that is important for tourism marketers. In this vein, this study aims to investigate tourist movement patterns in Europe. We acquired 122 data points from posts on the NAVER blog, which is the most famous social media platform in Korea. These data were transformed into matrix data for social network analysis and analyzed for centrality. The results suggest that Korean backpackers in Europe tend to enter Europe through London and Paris. Venezia and Firenze are also key cities.

Suggested Citation

  • Hee Chung Chung & Namho Chung & Yoonjae Nam, 2017. "A Social Network Analysis of Tourist Movement Patterns in Blogs: Korean Backpackers in Europe," Sustainability, MDPI, vol. 9(12), pages 1-19, December.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:12:p:2251-:d:121690
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    References listed on IDEAS

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    1. Yoonjae Nam & George Barnett & Daejoong Kim, 2014. "Corporate hyperlink network relationships in global corporate social responsibility system," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1225-1242, May.
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    3. Yoonjae Nam, 2015. "Institutional network structure of corporate stakeholders regarding global corporate social responsibility issues," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 1063-1080, May.
    4. Xia, Jianhong (Cecilia) & Zeephongsekul, Panlop & Packer, David, 2011. "Spatial and temporal modelling of tourist movements using Semi-Markov processes," Tourism Management, Elsevier, vol. 32(4), pages 844-851.
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    Cited by:

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    2. Deukhee Park & Sunmi Yun, 2023. "Comparing Tourism Activity Patterns Influenced by a Tourism Information Source: A Case of the Gyeonggi Province, South Korea," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    3. Cathrine Linnes & Holly Itoga & Jerome Agrusa & Joseph Lema, 2021. "Sustainable Tourism Empowered by Social Network Analysis to Gain a Competitive Edge at a Historic Site," Tourism and Hospitality, MDPI, vol. 2(4), pages 1-15, October.
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    6. Mateusz Naramski, 2020. "The Application of ICT and Smart Technologies in Polish Museums—Towards Smart Tourism," Sustainability, MDPI, vol. 12(21), pages 1-27, November.
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    8. Yong Gao & Chao Ye & Xiang Zhong & Lun Wu & Yu Liu, 2019. "Extracting Spatial Patterns of Intercity Tourist Movements from Online Travel Blogs," Sustainability, MDPI, vol. 11(13), pages 1-18, June.
    9. Angela Chantre-Astaiza & Laura Fuentes-Moraleda & Ana Muñoz-Mazón & Gustavo Ramirez-Gonzalez, 2019. "Science Mapping of Tourist Mobility 1980–2019. Technological Advancements in the Collection of the Data for Tourist Traceability," Sustainability, MDPI, vol. 11(17), pages 1-32, August.
    10. Chu, Chih-Peng & Chou, Yu-Hsin, 2021. "Using cellular data to analyze the tourists' trajectories for tourism destination attributes: A case study in Hualien, Taiwan," Journal of Transport Geography, Elsevier, vol. 96(C).

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