DC Field | Value | Language |
---|---|---|
dc.contributor.author | 윤승식 | - |
dc.contributor.author | 신민철 | - |
dc.contributor.author | 강주영 | - |
dc.date.issued | 2019-03 | - |
dc.identifier.issn | 1975-4256 | - |
dc.identifier.uri | https://aurora.ajou.ac.kr/handle/2018.oak/34986 | - |
dc.description.abstract | Competition among cities has become fierce with decentralization and globalization, and each city tries to establish a brand image of the city to build its competitiveness and implement its policies based on it. At this time, surveys, expert interviews, etc. are commonly used to establish city brands. These methods are difficult to establish as sampling methods an empirical component, the biggest component of a city brand. In this paper, therefore, based on the precedent research’s urban brand measurement and components, the words representing each city image property were extracted and relocated to five indicators to form the evaluation index. The constructed indicators have been validated through the review of three experts. Through the index, we analyzed the brands of four cities, Ulsan, Incheon, Yeosu, and Gyeongju, and identified the factors by using Topic Modeling and Word Cloud. This methodology is expected to reduce costs and monitor timely in identifying and analyzing urban brand images in the future. | - |
dc.language.iso | Kor | - |
dc.publisher | 한국IT서비스학회 | - |
dc.title | 텍스트 마이닝 기법을 활용한 도시 브랜드 평가방법론 연구 : 뉴스미디어를 중심으로 | - |
dc.title.alternative | A Study on City Brand Evaluation Method Using Text Mining : Focused on News Media | - |
dc.type | Article | - |
dc.citation.endPage | 171 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 153 | - |
dc.citation.title | 한국IT서비스학회지 | - |
dc.citation.volume | 18 | - |
dc.identifier.bibliographicCitation | 한국IT서비스학회지, Vol.18 No.1, pp.153-171 | - |
dc.subject.keyword | City Brand | - |
dc.subject.keyword | City Brand Image | - |
dc.subject.keyword | News | - |
dc.subject.keyword | Data Mining | - |
dc.subject.keyword | Text Mining | - |
dc.subject.keyword | Topic Modeling | - |
dc.subject.keyword | Word Cloud | - |
dc.type.other | Article | - |
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