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http://dx.doi.org/10.17661/jkiiect.2022.15.2.79

Regional Image Change Analysis using Text Mining and Network Analysis  

Jeong, Eun-Hee (Department of Regional Economics, Kangwon National University)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.15, no.2, 2022 , pp. 79-88 More about this Journal
Abstract
Social media big data includes a lot of information that can identify not only consumer consumption patterns but also local images. This paper was collected annually data including 'Samcheok' from 2015 to 2019 from Blog and Cafe of Naver and Daum in domestic portal site, and analyzed the regional image change after refining keyword which forms the regional image by performing text mining and network analysis. According to the research results, the regional image of 2015 was expressed with image cognitive elements of the nearby place name or place etc. such as 'Jangho Port', 'Donghae', and 'Beach'. However the regional image both 2016 and 2019 were changed with image cognitive elements of 'SamcheokSolbich' which is a special place within region. Therefore as the keywords related to the local image include 'Jangho Port' and Resort, which are the representative attractions of Samcheok, it can be seen that the infrastructure factor plays a big role in forming the local image. The significance test for the network data used the bootstrap technique, and the p-values in 2015, 2016, and 2019 were 0.0002, 0.0006, and 0.0002, respectively, which were found to be statistically significant at the significance level of 5%.
Keywords
Bootstrap; CONCOR analysis; Degree centrality analysis; Social Big data; Text mining;
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