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An Efficient Estimation of Place Brand Image Power Based on Text Mining Technology
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Sukjae Choi (Humanitas BigData Research Center, KyungHee University)
Jongshik Jeon (Humanitas BigData Research Center, KyungHee University)
Biswas Subrata (School of Management, KyungHee University)
Ohbyung Kwon (School of Management, KyungHee University)
Vol. 21, No. 2, Page: 113 ~ 129
10.13088/jiis.2015.21.2.113
Keywords
Text Mining, Brand Image, Location Brand, Keyword Analysis, Anholt’s Brand Index
Abstract
Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place’s location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt’s evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper’s methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability.
The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.
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텍스트마이닝 기반의 효율적인 장소 브랜드 이미지 강도 측정 방법
최석재 (경희대학교 후마니타스 빅데이터 연구센터)
전종식 (경희대학교 후마니타스 빅데이터 연구센터)
비스워스 수브르더 (경희대학교 일반대학원 경영학과)
권오병 (경희대학교 경영학과)
Keywords
텍스트마이닝, 브랜드 이미지, 장소 브랜드, 주제어 분석, 안홀트 인덱스
Abstract
장소 브랜딩은 특정 장소에 대한 의미 부여를 통해 장소성의 정체성 및 공동가치를 생성하며 가치 창출을 하는데 중요한 활동이며, 장소 브랜드에 대한 이미지 파악을 통해 이루어진다. 이에 마케팅, 건축학, 도시건설학 등 여러 분야에서는 인상적인 장소 브랜드의 이미지를 구축하기 위하여 많은 노력을 기울이고 있다. 하지만 설문조사를 포함한 대면조사 방법은 대부분 주관적인 작업이며 측정에 많은 인력 또는 고도의 전문 인력이 소요되어 고비용을 발생시키므로 보다 객관적이면서도 비용효과적인 브랜드 이미지 조사 방법이 필요하다. 이에 본 논문은 텍스트마이닝을 통하여 장소 브랜드의 이미지 강도를 객관적이고 저비용으로 얻는 방법을 찾는 것을 목적으로 한다. 제안하는 방법은 장소 브랜드 이미지를 구성하고 있는 요인과 그 키워드들을 관련 웹문서에서 추출하며, 추출된 정보를 통해 특정 장소의 브랜드 이미지 강도를 측정하는 방법이다. 성능은 안홀트 방법에서 평가에 사용하는 전세계 50개 도시 이미지 인덱스 순위와의 일치도로 검증하였다. 성능 비교를 위해 임의로 순위를 매기는 방법, 안홀트의 설문방식대로 일반인이 평가하는 방법, 본 논문의 방법을 사용하되 안홀트의 방법으로 학습한 것으로 유의한 것으로 추정되는 평가 항목만을 반영하는 방법과 비교하였다. 그 결과 제안된 방법론은 정확성, 비용효율성, 적시성, 확장성, 그리고 신뢰성 측면에서 우수함을 보일 수 있었다. 따라서 본 연구에서 제안한 방법론은 안홀트 방식에 상호 보완적으로 사용될 수 있을 것이다. 향후에는 장소 브랜드 이미지를 형성하는 속성 별로 등장횟수를 계산 한 후에 장소 브랜드에 대한 태도, 연상, 그리고 브랜드 자산과의 인과관계를 자동으로 파악할 수 있는 부분까지 구현하고 실증적 실험을 할 예정이다.
Cite this article
JIIS Style
Choi, S., J. Jeon, B. Subrata, and O. Kwon, "An Efficient Estimation of Place Brand Image Power Based on Text Mining Technology", Journal of Intelligence and Information Systems, Vol. 21, No. 2 (2015), 113~129.

IEEE Style
Sukjae Choi, Jongshik Jeon, Biswas Subrata, and Ohbyung Kwon, "An Efficient Estimation of Place Brand Image Power Based on Text Mining Technology", Journal of Intelligence and Information Systems, vol. 21, no. 2, pp. 113~129, 2015.

ACM Style
Choi, S., Jeon, J., Subrata, B., and Kwon, O., 2015. An Efficient Estimation of Place Brand Image Power Based on Text Mining Technology. Journal of Intelligence and Information Systems. 21, 2, 113--129.
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@article{Choi:JIIS:2015:615,
author = {Choi, Sukjae and Jeon, Jongshik and Subrata, Biswas and Kwon, Ohbyung},
title = {An Efficient Estimation of Place Brand Image Power Based on Text Mining Technology},
journal = {Journal of Intelligence and Information Systems},
issue_date = {June 2015},
volume = {21},
number = {2},
month = Jun,
year = {2015},
issn = {2288-4866},
pages = {113--129},
url = {http://dx.doi.org/10.13088/jiis.2015.21.2.113 },
doi = {10.13088/jiis.2015.21.2.113},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Text Mining, Brand Image, Location Brand, Keyword Analysis and Anholt’s Brand Index },
}
%0 Journal Article
%1 615
%A Sukjae Choi
%A Jongshik Jeon
%A Biswas Subrata
%A Ohbyung Kwon
%T An Efficient Estimation of Place Brand Image Power Based on Text Mining Technology
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 21
%N 2
%P 113-129
%D 2015
%R 10.13088/jiis.2015.21.2.113
%I Korea Intelligent Information System Society