DOI QR코드

DOI QR Code

Development of Demand Prediction Model for Video Contents Using Digital Big Data

디지털 빅데이터를 이용한 영상컨텐츠 수요예측모형 개발

  • Song, Min-Gu (Faculty of Liberal Arts, Yewon Arts University)
  • 송민구 (예원예술대학교 교양학부)
  • Received : 2022.03.31
  • Accepted : 2022.04.20
  • Published : 2022.04.28

Abstract

Research on what factors affect the success of the movie market is very important for reducing risks in related industries and developing the movie industry. In this study, in order to find out the degree of correlation of independent variables that affect movie performance, a survey was conducted on film experts using the AHP method and the importance of each measurement factor was evaluated. In addition, we hypothesized that factors derived from big data related to search portals and SNS will affect the success of movies due to the increase in the spread and use of smart phones. And a prediction model that reflects both the expert survey information and big data mentioned above was proposed. In order to check the accuracy of the prediction of the proposed model, it was confirmed that it was improved (10.5%) compared to the existing model as a result of verification with real data.Therefore, it is judged that the proposed model will be helpful in decision-making of film production companies and distributors.

영화 시장에서 흥행을 기록하는데 어떤 요인들이 영향을 미치는지에 대한 연구는 관련 산업의 리스크를 줄이고 영화 산업을 발전시키는데 매우 중요하다. 본 연구에서는 영화흥행에 영향이 있는 독립변수들의 상관의 정도를 찾아내기 위해서 먼저 AHP 기법을 이용한 영화전문가들에 대한 설문조사를 실시하여 측정요인별 중요도를 평가하였다. 또한, 스마트폰 보급과 사용의 증가로 검색 포털 및 SNS 관련 빅데이터에서 도출된 요인이 영화흥행에 영향을 미칠 것이라는 가설을 설정하였다. 그리고 앞에서 언급한 전문가 서베이 정보와 빅데이터를 모두 반영한 예측모형을 제안하였다. 제안한 모형의 예측의 정확도를 알아보기 위해 실 데이터를 가지고 검증한 결과 기존모형보다 향상됨(10.5%)을 확인하였다. 따라서 제안한 모형은 영화제작사 및 배급사들의 의사 결정에 도움이 될 것이라 판단된다.

Keywords

Acknowledgement

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2019S1A5A8037916).

References

  1. Variety. (2013) Big data : Media Embracing the Most Detailed Information about You yet. Retrieved from: http://variety.com/2013/biz/news/big-data-media-embracing-the-most-detailed-information-about-you-yet-12.
  2. Saaty. T. L. (2003). Decision-making with the AH P:Why is the Principal Eigen Vector Necessary. European Journal of Operational Research, 145(1), 85-91. https://doi.org/10.1016/S0377-2217(02)00227-8
  3. M. G. Song & S. B. Kim. (2013). A Study on the Improvement of the Reliability of a Predictive Model Using Big Data Analysis. Digital Policy Research, 11(6), 03-112.
  4. S. O. Kim. (2018). Predicting of Financial Success Using Data Analysis for Korean Movies. Master's Thesis. Soongsil University, 1-23.
  5. Y. H. Kim & J. H. Hong. (2011). A Study for the Development of Picture Box-office Prediction Model. Proceedings of the Korean Statistical Society, 18(6), 859-869. DOI: 10.5351/CKSS.2011.18.6.859
  6. S. H. Lee. (2015). A Study on Predicting Movie Performance Using Text Mining. Journal of Korean Data Information Science Society, 26(6), 1259-1269. https://doi.org/10.7465/jkdi.2015.26.6.1259
  7. O. J Lee. (2014). Analysis of Movie Box Office Success Factors Using Social Big Data. Journal of the Korean Contents Association, 14(10), 527-538. https://doi.org/10.5392/JKCA.2014.14.10.527
  8. S. Y. Park. (2012). Effect of Word of Mouth Effect on Movie Box Office through SNS - Focusing on Sunny's Case. Journal of the Korean Contents Association, 12(7), 40-53. https://doi.org/10.5392/JKCA.2012.12.07.040
  9. M. G. Song. (2016). The Suggestion of Big Data Platform for the Strengthening of Privacy and Enabled of Big Data. Journal of Digital Convergence, 14(12), 155-164. DOI: 10.14400/JDC.2016.14.12.155
  10. S. J. Oh & C. H. Kim. (2016). Web Drama Analysis and Suggestion Using Social Media Big Data Mining and Opinion Mining Techniques. Korean Society of Cartoon and Animation Studies, (44), 285-306. DOI: 10.7230/KOSCAS.2016.44.285
  11. J. P. Ou & O. H. Lee. (2018). A Model of Predictive Movie 10 Million Spectators through Big Data Analysis. Journal of the Korean Big Data Society, 203(1), 63-71. DOI: 10.36498/kbigdt.2018.3.1.63
  12. H. L. Lee & G. H. Cho. (2013). A Study on Developing the Design Quality Indicator for School Building-Using Delphi Survey Method and AHP. Journal of the Korean Institute of Architecture, 28(5), 69-77.
  13. S. Y. Lee & H. J. Yun. (2019). A Study on Data Information System Based on Artifical Intelligence. Journal of the KICES, 14(2), pp. 377-388.
  14. J. W. Kim. (2020). Analyzing Factors of Success of Film Using Big Data. Journal of Korean Entertainment Industry Association, 14(4), 145-153. https://doi.org/10.21184/jkeia.2020.6.14.4.145