• Title/Summary/Keyword: 구글트렌드지수

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A Model of Predictive Movie 10 Million Spectators through Big Data Analysis (빅데이터 분석을 통한 천만 관객 영화 예측 모델)

  • Yu, Jong-Pil;Lee, Eung-hwan
    • The Journal of Bigdata
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    • v.3 no.1
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    • pp.63-71
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    • 2018
  • In the last five years (2013~2017), we analyzed what factors influenced Korean films that have surpassed 10 million viewers in the Korean movie industry, where the total number of moviegoers is over 200 million. In general, many people consider the number of screens and ratings as important factors that affect the audience's success. In this study, four additional factors, including the number of screens and ratings, were established to establish a hypothesis and correlate it with the presence of 10 million spectators through big data analysis. The results were significant, with 91 percent accuracy in predicting 10 million viewers and 99.4 percent accuracy in estimating cumulative attendance.

Exploring the leading indicator and time series analysis on the diffusion of big data in Korea (빅데이터 확산에 대한 선행 데이터 탐색 및 국내 확산 과정의 시계열 분석)

  • Choi, Jin;Kim, YoungJun
    • Journal of Technology Innovation
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    • v.26 no.4
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    • pp.57-97
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    • 2018
  • Big Data has spread rapidly in various industries since 2010. We analyzed the general characteristics of big data through time series analysis on the initial process of spreading big data and investigated the difference of diffusion characteristics in each industry. By analyzing papers, patents, news data, and Google Trend using Big Data as a keyword, we searched for data corresponding to the leading indicator, and confirmed that trends in news and Google Trend preceded the papers and patents by two years. We used Google Trend to compare the introduction period of domestic, US, Japan, and China and quantify the process of spreading the eight main industries in Korea through news data. Through this study, we present an empirical research method on how the general technology spreads in several industry sectors and we have figured out where the spreading speed difference of big data originated in each industry in Korea. The method presented here can be used to analyze the technology introduced from foreign countries in developing countries because it can be analyzed in diffusion process of other technologies besides big data and corresponds to the diffusion of technology keywords in a specific country. And, on the corporate side, this approach shows what path is effective when it comes to launching and spreading new technologies.