TRENDS IN OVERTOURISM RESEARCH FROM 2018 TO 2021: TEXT MINING AND SEMANTIC NETWORK ANALYSIS

초록

This research aimed to examine overtourism-related papers published in the Web of Science and to identify research structure framework through network analysis between key keywords. Accordingly, the abstract of 110 papers related to overtourism from 2018 to 2021 was reviewed through text mining using Python. Afterwards, clusters derived through semantic network analysis were found to be Positive/Negative Impact of Tourism Development, Economic Causes, Efforts for Sustainability," and Necessity of Policy. Through this, it was intended to present countermeasures against overtourism and directions for establishing policies. In addition, by deriving the main keywords for each cluster, basic data that can examine the relationship between overtourism phenomena in more detail were provided and contributed to the literature.

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