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Image Analysis and Management Strategy for The National Science Museum Utilizing SNS Big Data Analysis

SNS 빅데이터 분석을 활용한 국립과학관에 대한 이미지 분석과 경영전략 제안

  • Shin, Seongyeon (Korea Institute of Sport Science, Korea Sports Promotion foundation)
  • 신성연 (국민체육진흥공단 한국스포츠정책과학원)
  • Received : 2019.08.26
  • Accepted : 2020.01.03
  • Published : 2020.01.31

Abstract

The purpose of this study is to investigate science consumers' perceptions of the National Science Museum and suggest effective management strategies for the museum. Research questions were established and the analyses were conducted to achieve the research goals. The collection and analysis of the data were conducted through a new approach to image analysis that combines qualitative and quantitative methods. First, the image of the concept of science was derived from science consumers (adults, undergraduate and graduate students) through a qualitative research method (group-interviewing), and then text analysis was conducted. Second, quantitative research was conducted through LDA (Latent Dirichlet Allocation)-based topical modeling of 63,987 words extracted from 12,920 titles of blog postings from one of the most heavily-trafficked portal sites in Korea. The results of this study indicate that the perception of science differs according to the characteristics of the respondents. Further, topic-modeling extracted 20 topics from the blog posting titles and the topics were condensed into seven factors. Detailed discussions and managerial implications are provided in the conclusion section.

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