한국융합학회논문지 (Journal of the Korea Convergence Society)

  • 제9권4호
  • /
  • Pages.15-22
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  • 2018
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  • 2233-4890(pISSN)
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  • 2713-6353(eISSN)
한국융합학회 (Korea Convergence Society)
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빅데이터 분석을 통한 패키징에 대한 소비자의 주요 인식 조사 -텍스트 마이닝과 의미연결망 분석을 중심으로-

A Study of the Consumer Major Perception of Packaging Using Big Data Analysis -Focusing on Text Mining and Semantic Network Analysis-

  • 강욱건 (연세대학교 패키징학과) ;
  • 고의석 (연세대학교 패키징학과) ;
  • 이학래 (연세대학교 패키징학과) ;
  • 김재능 (연세대학교 패키징학과)
  • 투고 : 2018.02.14
  • 심사 : 2018.04.20
  • 발행 : 2018.04.28
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초록

패키징에 대한 소비자들의 주요인식을 조사하기 위해 빅데이터 분석방법인 텍스트 마이닝과 의미연결망 분석을 중심으로 연구를 진행하였다. 데이터 수집은 웹&SNS데이터 분석 프로그램인 텍스톰(Textom)을 사용하여 2년 7개월간의 데이터를 수집하였다. 연구 결과 네트워크 중심도는 패키징의 경우 8.9% 포장은 9.1%로 패키징이 보다 다양한 주제를 다루는 것으로 조사되었다. CONCOR 분석을 통해서 유사한 의미를 가지는 4개의 그룹으로 분류하여 패키징에 관한 소비자들의 주요인식을 연구, 개발, 산업, 소재, 기능 등으로 요약하였다. 본 연구에 따르면 소비자가 가장 많이 인식하는 패키징 소재는 합성수지이며 패키징 기능으로는 보관의 기능을 주로 인식한다. 또한 소비자들이 인식하는 패키징 관련 상품군으로 제약, 의약품인 것으로 조사되었다. 본 연구결과는 패키징에 대한 소비자들의 인식을 예측함으로써 향후 이루어질 연구와 산업발전에 기초자료로써의 활용 가능성을 가지며 빅데이터와 패키징 두 분야의 융합을 통한 패키징 분야의 새로운 연구방향을 제시한 의의가 있다.

The purpose of this study is to investigate the consumer perception of packaging using big data analysis. This study use text mining to extract meaningful words from text and semantic network analysis to analyze connectivity and propagation trends. Data were collected by dividing the 'packaging(Korean)' and 'packaging(English)'. This study visualized the word network structure of the two key words and classified them into four groups with similar meaning through CONCOR analysis. The group name was specified based on the words constituting the classified group. These groups are a major category of consumers' perception of packaging. Especially cosmetics and design have high frequency of words and high centrality. Therefore it can be expected that the packaging design is perceived as important in the cosmetics industry. This study predicts consumers' perception of packaging so it can be a basis for future research and industry development.

키워드

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