English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A good tourism image can significantly enhance the travel willingness and experience of international tourists. Most related research focused on the tourism image perception of world-famous cities, but research on the tourism image of North Korea is insufficient. We extracted text data from travel notes and reviews on Chinese travel websites. Subsequently, we used text mining and semantic network analysis to investigate Chinese tourists’ perception of the tourism image of North Korea. The results of the semantic network analysis show that tourism in North Korea consisted mainly of visits to the main cities and famous scenic spots, always with tour guides. Changes in high-frequency words indicated that Chinese tourists’ interest in North Korea’s history has weakened in recent years, and their interest in scenic spots and tourism products has increased. The results of the iterative correlation convergence analysis show that the topics relevant to tourists’ image of North Korea are composed of representative scenic spots, the Korean War, Kaesong city, the Pyongyang City, people’s lives, and other notable experiences. This research makes an empirical case for the study of tourists’ perception of the tourism image of North Korea and provides targeted suggestions for the sustainable development of North Korean tourism.

Chinese Tourists’ Perception of the Tourism Image of North Korea Based on Text Data from Tourism Websites