감성과학 (Science of Emotion and Sensibility)

  • 제20권4호
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  • Pages.31-40
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  • 2017
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  • 1226-8593(pISSN)
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  • 2383-613X(eISSN)
한국감성과학회 (Korean Society for Emotion and Sensibility)
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한국 드라마 수용에 있어서 국가별 감정 반응 분석: 드라마 <도깨비>를 중심으로

A Comparative Study of Emotional Response to Korean Drama among Countries: With Drama 'Goblin'

  • Lee, Yewon (Graduate School of Culture Technology, KAIST) ;
  • Woo, Sungju (Graduate School of Culture Technology, KAIST)
  • 투고 : 2017.06.12
  • 심사 : 2017.11.03
  • 발행 : 2017.12.31
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초록

본 연구는 한류 콘텐츠 소비 시 나타나는 한국, 일본, 미국의 감정 반응을 통해 국가별 소비 성향을 규명하는 데 목적이 있다. 방대해진 텍스트 리뷰를 이용한 감정 분석 연구가 주목받고 있고, 콘텐츠 수요에 환경적 특성이 주요한 영향을 주고 있음에도, 국가별 감정 반응 차이에 대한 연구는 거의 이루어지지 않고 있다. 따라서 본 연구에서는, Russell(1980)이 제시한 감정 원형 모델을 사용하여 한국형 판타지 멜로드라마 <도깨비>에 대한 국가별 감정 단어의 변수 중요도 및 단어 간 연관을 비교하였다. 우선, 2017년 1월 26일부터 3월 26일까지 2달간의 텍스트 리뷰를 수집하였다. 둘째, 수집한 데이터로부터 Russell의 감정 모델에 해당하는 감정 단어를 선별하였다. 셋째, 선별한 데이터에 랜덤 포레스트를 적용하여 변수 중요도를 평가하였다. 넷째, Russell 축에 따른 주요 감정 단어 간 연관성을 비교하였다. 마지막으로 테스트 데이터를 이용하여 학습된 모델의 정확성을 측정하였다. 실험 결과, 국가별 감정 단어의 변수 중요도에서 한국과 미국은 Happy, 일본은 Pleased가 가장 중요한 변수로 나타남을 확인하였다. 단어 간 연관성에서 한국은 수동적 불쾌감, 미국과 일본은 수동적 쾌감이 강하게 나타나는 경향이 있음을 확인하였다. 본 연구를 통해, 한류 콘텐츠에 대한 국가별 감정 반응 차이를 확인할 수 있을 것으로 기대한다.

This research aims to investigate 'Hallyu' contents consumption tendency of consumers from Korea, Japan, and the United States by analyzing their emotional responses. With the development of social media, research on emotion analysis by reviewing text materials has grown. Whereas environmental variables affect consumer demand towards 'Hallyu' contents, little comparative analyses have been conducted on the emotional responses of consumers from different countries. In this research, the emotional prototype model proposed by Russell(1980) used to extract and distinguish emotional words to clarify how people in the three countries differently perceive the Korean drama "Goblin". First of all, the SNS reviews were collected during a two-month period (February 12 to April 12). Second, significant factors were identified in the collected data according to Russell's emotion model. Third, random forest was applied to organize the selected variables in the order of variable importance. Fourth, the correlations among the emotional words were compared. Lastly, the accuracy of the trained model was measured using the test dataset. The results show that "Happy" was found to be the greatest factor in Korea and in the United States and "Pleased" in Japan. Emotional words correlations showed that when watching the drama "Goblin", "passive unpleasure" was the main factor associated with individual's interest in Korea whereas "passive pleasure" was associated with individual's interest in Japan and in the United States. Based on the results, this research suggests the possibility of developing evaluation guidelines for emotional responses of different countries towards 'Hallyu' contents.

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참고문헌

  1. Baccianella, S., Andrea, E., & Fabriziom S. (2010). SentiWordNet3.0: An enhanced lexical resource forsentiment analysis and opinion mining. In Proceedings of the Seventh Conferenceon International Language Resources andEvaluation (LREC'10), 2200-2204.
  2. Bae, I. H., & Kim, H. S. (2011). A korean wave diffusion strategy through success of culture contents in thailand. Journal of Product Research, 29(5), 21-32. DOI: 10.6115/fer.2017.012
  3. Bartsch, A., Appeal, M., & Storch, D. (2010). Predicting emotions and meta-emotions at the movies: The role of the need for affect in audiences' experience of horror and drama. Communication Research, 37(2), 167-190. DOI: 10.1177/0093650209356441
  4. Biau, G., & Scornet, E. (2016) A random forest guided tour. Test, 25(2), 197-227. DOI: 197-227.10.1007/s11749-016-0481-7
  5. Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5-32. DOI: 10.1023/A:101093340
  6. Cho, B. C., & Sim, H. C. (2013). Sucess factor analysis of K-POP and a study on sustainable korean wave: Focus on smart media based on realistic contents. Journal of the Korea Contents Association, 13(5), 90-102. DOI: 10.5392/JKCA.2013.13.05.090
  7. Chon, B. S. (2005). Genre preferences for domestic and foreign television programs. Korean Journal of Broadcasting and Telecommunication Studies, 19(3), 209-241.
  8. Eisenberg, N., Cumberland, A., & Spinard, T. L. (1998). Parental socialization of emotion. Psychological Inquiry, 9, 241-273. DOI: 10.1207/ s15327965pli0904_1
  9. Feldman, D. C., & Turnley, W. H. (1995). Underemployment among recent business college. Journal of Organizational Behavior, 16, 691-706. DOI: 10.1002/job.4030160708
  10. Ho, T. K. (1995). Random decision forests. Proc. 3rd Int. Document Analysis and Recognition, 1, 278-282. DOI: 10.1109/icdar.1995.598994
  11. Hwangbo, H. W., & Kim, J. H. (2016). A study on the factors affecting to the export performance for korean drama using sentimental analysis. The e-Business Studies, 17(6), 87-99. DOI: 10.20462/TeBS.2016.12.17.6.87
  12. Im, Y. J., Jang, H. W., & Kim, S. H. (2010). Research models for predicting foreign tourists behavior toward korean wave cultural contents: Focused on Theory of Planned Behavior (TPB). Korean Journal of Tourism Research, 24(6), 131-149.
  13. Jang, K. A., Park, S. H., & Kim, W. J. (2015). Automatic construction of a negative/positive corpus and emotional classification using the internet emotional sign. Journal of KIISE, 42(4), 512-521. DOI: 10.5626/jok.2015.42.4.512
  14. Jin, Y. H., Hong, K. W., & Kim, H. J. (2000). A Study on the research consumer's action style and important proper degree at the select fast food. Culinary Science & Hospitality Research, 6(3), 167-192.
  15. Kim, B. K., Hong, S. J., Oh, J. I., Lee, S. K., Kim, G. C., & Kang, M. C. (2014). A study on global strategy for expanding korean broadcasting market. Korea Communications Commission.
  16. Kim, J. O. (2012). Impact analysis of nonverbal multimodals for recognition of emotion expressed virtual humans. Journal of Korean Society for Internet Information, 13(5), 9-19. DOI: 10.7472/jks ii.2012.13.5.9
  17. Kim, M. H., Jang, H. Y., Jo, Y. M., & Shin. H, P. (2013). KOSAC: Korean Sentiment Analysis Corpus. Korean Institute of Information Scientists and Engineers, 2013(6), 650-652.
  18. Kim, W. S., Ham, J. S., Sohn, C. Y., Yun, J. S., Lim, C., & Ko, I. J. (2010). Measurement of emotional transition using physiological signals of audiences. Journal of the Korea Contents Association, 10(8), 168-176. DOI: 10.5392/jkca.2010.10.8.168
  19. Ko, J. M. (2009). The Korean Wave Across Asia and Throughout the World. Korea Foundation for International Culture Exchange.
  20. Ko, J. M. (2012). A study on the internationalization of Korean cultural industry. Humanities Contents, 27, 143-154.
  21. Kwon, Y. H. (2005). The effects of affective responses and attitude toward TV film on destination image formation. Journal of Tourism Sciences, 28(4), 335-356.
  22. Lee, C. S., Choi, D. H., Kim, S. S., & Kang, J. W. (2013). Classification and analysis of emotion in Korean microblog texts. Korea Information Science Society, 40(3), 159-167.
  23. Lee, E. K., Suh, E. K., Thai C., Kim, H. J., & David, K. S, (2009). Is emotion suppression that bad? Comparing the emotion suppression and subjective well-being link in two cultures. The Korean Journal of Social and Personality Psychology, 23(1), 131-146.
  24. Lee, S. H. (1998). An empirical study on the process of consumption emotion. Master's Thesis, Seoul National University, Seoul, Korea, 4.
  25. Lee, Y. S. (2011). Effect of toruism image on tourism motivation and experientiality of chinese tourists' on korean wave. Journal of the Korea Contents Association, 11(1), 387-395. DOI: 10.5392/jkca.2011.11.1.387
  26. Moon, H. J., & Park, S. H. (2013). An exploratory study the popular factors and likability of korean wave. Journal of international Area Studies, 17(3), 19-47. DOI: 10.18327/jias.2013.10.17.3.19
  27. Ortony, A., & Turner, T. (1990). What's basic about basic emotion?. Psychological Review, 97(3), 315-331. DOI: 10.1037//0033-295x.97.3.315
  28. Russell, J. A. (1980). A circumplex model of affect. Journal of Personalityand Social Psychology, 39, 1161-1178. DOI: 10.1037/h0077714
  29. Shoda, H., Nitta, H., Suzuki, N., Kishimoto, W., & Sakata, M. (2015). Audio-visual interaction in the emotion perception of face and voice: Analyses of emotion judgment and reaction time. Cognitive Studies, 22(3), 480-485. DOI: 10.11225/jcss.22.480
  30. Song, H. S. (2011). A study on the relation between emotion and color in healing video Art. The Treatise on The Plastic Media, 14(3), 79-86.
  31. Thet, T. T., Na, J. C., & Khoo, C. (2010). Aspect-based sentiment analysis of movie reviews on discussion boards. Journal of Information Science, 36(6), 823-848. DOI: 10.1177/0165 551510388123