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Projected and Perceived Destination Images of the Tsunami Memorial Parks After the Great East Japan Earthquake: A Text Mining Analysis

Author

Listed:
  • Sihan Zhang

    (Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan)

  • Qian Wang

    (Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan)

  • Prudens Naura Afzelia

    (Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan)

  • Yan Tang

    (Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan)

  • Yilan Xie

    (Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan)

  • Jing Zhang

    (Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan)

  • Yusuke Matsuyama

    (Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan)

  • Katsunori Furuya

    (Graduate School of Horticulture, Chiba University, 648, Matsudo 271-8510, Chiba, Japan)

Abstract

Following the Great East Japan Earthquake, dark tourism was developed in the Tohoku Region of Japan. Notably, two government-built tsunami memorial parks in Ishinomaki and Rikuzentakata have obtained attention for their profound disaster narratives, iconic disaster sites, and expansive layouts. This study is the first to compare the projected destination image presented by destination management organizations with the perceived destination image held by visitors in these parks, and in dark tourism. Using online text data from both supply and demand sides of dark tourism and text mining analyses such as word frequency analysis, co-occurrence network analysis, and affection tendency examination, we revealed similarities and disparities between these two perspectives. Furthermore, this study concluded dimensions specific to dark tourism sites within the cognitive and affective destination image. Based on the findings, the study provides advice for destination managers to improve these sites, including developing non-dark tourism products and improving infrastructures. Additionally, it proposes placing greater emphasis on themes of revitalization and future development, while fostering visitor engagement in local non-profit and citizen activities to strengthen connections with residents. The findings demonstrate the effectiveness of text mining in comparing projected and perceived destination images in the context of dark tourism sites.

Suggested Citation

  • Sihan Zhang & Qian Wang & Prudens Naura Afzelia & Yan Tang & Yilan Xie & Jing Zhang & Yusuke Matsuyama & Katsunori Furuya, 2024. "Projected and Perceived Destination Images of the Tsunami Memorial Parks After the Great East Japan Earthquake: A Text Mining Analysis," Land, MDPI, vol. 13(12), pages 1-23, November.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:12:p:2034-:d:1531581
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    References listed on IDEAS

    as
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    3. Sihan Zhang & Ryo Nishisaka & Shixian Luo & Jing Xie & Katsunori Furuya, 2024. "The Interplay between Citizen Activities and Space across Different Official Memorial Landscape Construction Phases: Disaster Risk Reduction in Ishinomaki, Japan," Land, MDPI, vol. 13(7), pages 1-28, July.
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