디지털콘텐츠학회 논문지 (Journal of Digital Contents Society)

  • 제18권8호
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  • Pages.1537-1542
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  • 2017
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  • 1598-2009(pISSN)
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  • 2287-738X(eISSN)
한국디지털콘텐츠학회 (Digital Contents Society)
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영화 대본에서 감정 및 정서 분석: 사례 연구

Emotion and Sentiment Analysis from a Film Script: A Case Study

  • 유혜연 (성균관대학교 컴퓨터공학과) ;
  • 김문현 (성균관대학교 컴퓨터공학과) ;
  • 배병철 (홍익대학교 게임학부)
  • 투고 : 2017.12.12
  • 심사 : 2017.12.25
  • 발행 : 2017.12.31
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초록

감정은 서사 생성과 이해 모두에서 중요한 역할을 한다. 본 논문은 플루칙의 감정 모델을 기반으로 영화 대본에서 8가지 감정 표현을 분석하였다. 먼저 각 장면별 수동으로 감정을 태깅하였고, 이 때 8가지 감정 중 분노, 공포, 그리고 놀람이 가장 우세하게 나타났는데, 이는 스릴러 영화 장르를 고려할 때 의미있다고 할 수 있다. 또한, 스토리에서 긴장이 가장 고조되는 클라이맥스에서 다양한 감정이 복합적으로 나타난다고 가정하였고, 대본 상에서 3 부분의 클라이맥스를 확인할 수 있었다. 그 다음으로 파이썬 (Python) 프로그래밍 언어 기반 자연어처리 도구인 NLTK (Natural Language ToolKit)의 감성 분석 도구를 이용하여 수동 감정 태깅과 비교한 결과, 분노와 공포 감정에서 높은 일치율을, 그리고 놀람, 기대, 혐오 감정에서는 낮은 일치율을 보임을 확인하였다.

Emotion plays a key role in both generating and understanding narrative. In this article we analyzed the emotions represented in a movie script based on 8 emotion types from the wheel of emotions by Plutchik. First we conducted manual emotion tagging scene by scene. The most dominant emotions by manual tagging were anger, fear, and surprise. It makes sense when the film script we analyzed is a thriller-genre. We assumed that the emotions around the climax of the story would be heightened as the tension grew up. From manual tagging we could identify three such duration when the tension is high. Next we analyzed the emotions in the same script using Python-based NLTK VADERSentiment tool. The result showed that the emotions of anger and fear were most matched. The emotion of surprise, anticipation, and disgust, however, scored lower matching.

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참고문헌

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