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The social construction of tourism online destination image: A comparative semiotic analysis of the visual representation of Seoul

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  • Hunter, William Cannon

Abstract

This study examines the destination image of Seoul as represented by photographs online, and compares it to the traditional projected image found in printed brochures and guidebooks by replicating a previous study. Using visual semiotics, the social construction of tourism online destination image is investigated in terms of denotative and connotative signs. Using language-specific keyword searches, ‘Seoul travel’ on Naver, Google and Baidu, three demographic perspectives were examined including Korean, international English speaking and, Chinese. It was found that these different online contexts represent Seoul in different ways. Naver represents Seoul in more detail; Google and Baidu represent a mix of other destinations with Seoul connoting differences in perception, or reflecting the constraints of individual or group travel. The major findings suggest that the organic online self-representation of individual travel experiences by travelers, makes tourism as a soft power more effective, by supplementing the projected image of Seoul.

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  • Hunter, William Cannon, 2016. "The social construction of tourism online destination image: A comparative semiotic analysis of the visual representation of Seoul," Tourism Management, Elsevier, vol. 54(C), pages 221-229.
    • Handle: RePEc:eee:touman:v:54:y:2016:i:c:p:221-229
    DOI: 10.1016/j.tourman.2015.11.012
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    1. Stepchenkova, Svetlana & Zhan, Fangzi, 2013. "Visual destination images of Peru: Comparative content analysis of DMO and user-generated photography," Tourism Management, Elsevier, vol. 36(C), pages 590-601.
    2. Sharon Zukin, 1998. "Urban Lifestyles: Diversity and Standardisation in Spaces of Consumption," Urban Studies, Urban Studies Journal Limited, vol. 35(5-6), pages 825-839, May.
    3. Hunter, William Cannon, 2013. "China's Chairman Mao: A visual analysis of Hunan Province online destination image," Tourism Management, Elsevier, vol. 34(C), pages 101-111.
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    Cited by:

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    2. Yuanxiang Peng & Ping Yin & Kurt Matzler, 2022. "Analysis of Destination Images in the Emerging Ski Market: The Case Study in the Host City of the 2022 Beijing Winter Olympic Games," Sustainability, MDPI, vol. 14(1), pages 1-18, January.
    3. Vo Viet Hung & Sandeep Kumar Dey & Zuzana Vaculcikova & Le Trieu Hoang Anh, 2021. "The Influence of Tourists’ Experience on Destination Loyalty: A Case Study of Hue City, Vietnam," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    4. Li, Mimi & Wang, Yi & Wan, Yan & Huang, Xiaoting & Yang, Yihan, 2023. "The meaning of travel: Anecdotes from children," Annals of Tourism Research, Elsevier, vol. 103(C).
    5. Chang Li & Pengcheng Li & Xiaohui Huang, 2022. "Liked and Disliked Streetscape Imagery: Relation to Emotional Motivation and Block Distribution From Tourist Bus Visitors," SAGE Open, , vol. 12(3), pages 21582440221, August.
    6. Lourenção, Marina & de Moura Engracia Giraldi, Janaina & de Oliveira, Jorge Henrique Caldeira, 2020. "Destination advertisement semiotic signs: Analysing tourists' visual attention and perceived ad effectiveness," Annals of Tourism Research, Elsevier, vol. 84(C).
    7. Molinillo, Sebastian & Liébana-Cabanillas, Francisco & Anaya-Sánchez, Rafael & Buhalis, Dimitrios, 2018. "DMO online platforms: Image and intention to visit," Tourism Management, Elsevier, vol. 65(C), pages 116-130.
    8. Yan Yang & Chunfa Sha & Wencheng Su & Edwin Kofi Nyefrer Donkor, 2022. "Research on Online Destination Image of Zhenjiang Section of the Grand Canal Based on Network Content Analysis," Sustainability, MDPI, vol. 14(5), pages 1-20, February.
    9. Mak, Athena H.N., 2017. "Online destination image: Comparing national tourism organisation's and tourists' perspectives," Tourism Management, Elsevier, vol. 60(C), pages 280-297.
    10. Palazzo, Maria & Vollero, Agostino & Vitale, Pierluigi & Siano, Alfonso, 2021. "Urban and rural destinations on Instagram: Exploring the influencers’ role in #sustainabletourism," Land Use Policy, Elsevier, vol. 100(C).
    11. Hailong Wu & Takamitsu Jimura, 2019. "Exploring an Importance–Performance Analysis approach to evaluate destination image," Local Economy, London South Bank University, vol. 34(7), pages 699-717, November.
    12. Wei Sun & Shoulian Tang & Fang Liu, 2021. "Examining Perceived and Projected Destination Image: A Social Media Content Analysis," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    13. Dan Zhu & Jiayi Wang & Meifang Wang, 2022. "Sustainable Tourism Destination Image Projection: The Inter-Influences between DMOs and Tourists," Sustainability, MDPI, vol. 14(5), pages 1-16, March.
    14. Narcís Bassols-Gardella & Lluís Coromina, 2022. "The perceived image of multi-asset tourist destinations: investigating congruence across different content types," Service Business, Springer;Pan-Pacific Business Association, vol. 16(1), pages 57-75, March.
    15. Ralf Buckley & Mary-Ann Cooper, 2021. "Assortative Matching of Tourists and Destinations: Agents or Algorithms?," Sustainability, MDPI, vol. 13(4), pages 1-10, February.
    16. Paül i Agustí, Daniel, 2018. "Characterizing the location of tourist images in cities. Differences in user-generated images (Instagram), official tourist brochures and travel guides," Annals of Tourism Research, Elsevier, vol. 73(C), pages 103-115.
    17. Deng, Ning & Li, Xiang (Robert), 2018. "Feeling a destination through the “right” photos: A machine learning model for DMOs’ photo selection," Tourism Management, Elsevier, vol. 65(C), pages 267-278.
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