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KMID : 0665420200350010065
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Korean Journal of Food Culture
2020 Volume.35 No. 1 p.65 ~ p.78
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Analyzing Research Trends of Food Tourism Using Text Mining Techniques
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Shin Seo-Young
Lee Bum-Jun
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Abstract
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The objective of this study was to review and evaluate the growing subject of food tourism research, and thus identify thetrend of food tourism research. Using a Text mining technique, this paper discovered the trends of the literature on foodtourism that was published from 2004 to 2018. The study reviewed 201 articles that include the words ‘food’ and ‘tourism’in their abstracts in the KCI database. The Wordscloud analysis results presented that the research subjects werepredominantly ‘Festival’, ‘Region’, ‘Culture’, ‘Tourist’, but there was a slight difference in frequency according to the timeperiod. Based on the main path analysis, we extracted the meaningful paths between the cited references publisheddomestically, resulting in a total of 12 networks from 2004 to 2018. The Text network analysis indicated that the words withhigh centrality showed similarities and differences in the food tourism literature according to the time period, displaying themin a sociogram, a visualization tool. This study has implications that it offers a new perspective of comprehending the overallflow of relevant research.
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KEYWORD
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Food tourism, research trend, text mining, main path analysis, wordcloud analysis, text network analysis
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