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Clustering Corporate Brands based on Opinion Mining: A Case Study of the Automobile Industry

오피니언 마이닝을 통한 브랜드 클러스터링: 자동차 산업 사례연구

  • Received : 2016.07.29
  • Accepted : 2016.11.10
  • Published : 2016.11.30

Abstract

Since the Internet provides a way of expressing and sharing Internet users' mindsets, corporate marketers want to acquire measurable and actionable insights from web data. In the past, companies used to analyze the attitude, satisfaction, and loyalty of consumers toward their brands using survey data, whereas nowadays this is done using the big data extracted from Social Network Services. In this study, we propose a framework for clustering brand names using the social metrics gathered on social media. We also conduct a case study of the automobile industry to verify the feasibility of the proposed framework. We calculate the brand name distance for each pair of brand names based on the total number of times that they are mentioned together. These distances are used to project the brand name onto a 3-dimensional space using multidimensional scaling. After the projection, we found the clusters of brand names and identified the characteristics of each cluster. Furthermore, we concluded this paper with a discussion of the limitations and future directions of this research.

Keywords

Automobile Industry;Brand clustering;Multidimensional Scaling;Opinion Mining;Social Media

Acknowledgement

Supported by : 한림대학교, 정보통신기술진흥센터

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