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

被引：0

作者：

Tang, Ruohan ^{[1
]}

Lee, Won Seok ^{[2
]}

Moon, Joonho ^{[3
]}

Shim, Ji Min ^{[4
]}

机构：

[1] Liaocheng Univ, Sch Hist Culture & Tourism, Liaocheng, Shandong, Peoples R China

[2] Kyonggi Univ, Dept Tourism & Recreat, Seoul, South Korea

[3] Kangwon Natl Univ, Dept Tourism Adm, Chunchon, South Korea

[4] Kyonggi Univ, Dept Leisure & Tourism Sci, 24 Kyonggidae Ro 9 Gil, Seoul, South Korea

来源：

TOURISM REVIEW INTERNATIONAL | 2023年 / 27卷 / 3-4期

关键词：

Overtourism; Text mining; Semantic network analysis; Sustainability; TOURISM; EXPERIENCE; KOREA;

D O I：

10.3727/154427223X16890979065884

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：187 / 200

页数：14

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