A study on the recognition of Korea National Park by using social network analysis based on big data

Abstract

The purpose of this studies to generate the tourist's perception of National Park in Korea by using social network analysis based on big data. Data were gathered from Naver, Daum, and Google as analysis of data channels. The search period was limited to three years from Jan.1, 2018, to Dec.31, 2020. a total of 30,183 text data were collected by using the Textom program, and keywords analysis and frequency analysis of the data collected through text mining was performed to identify Korea National park. Density analysis, network concentration analysis, centrality analysis, and CONCOR analysis were performed using the Ucinet 6 program. As a result, first, various keywords related to Korea National Park such as ‘National Park Service, Ministry of Environment, hiking, trail, travel, sunrise, picture, autumn, sunset, beautiful’ were extracted. Second, as a result of CONCOR analysis, finally, 4 groups were formed. Confidently, this study discussed the implications of a marketing strategy for Korea’s National Parks as a result of the semantic network analysis study. Therefore, the activation of National Park, which is a typical tourism form of sustainable tourism, is expected to be an alternative to the tourism industry in Korea.