通过对电影的大规模计算分析来衡量好莱的多样性
David Bamman1, Rachael Samberg2, Richard Jean So3
1School of Information, University of California, Berkeley, CA 94704.
概括
研究人员利用新的法律框架分析了2,307部电影,揭示了好莱电影中性别和种族/民族代表性的趋势. 计算方法证实,随着时间的推移,多样性增加.
科学领域:
- 计算社会科学 计算社会科学
- 媒体研究 媒体研究
- 电影分析 电影分析
背景情况:
- 电影的计算研究在美国受到版权法的限制.
- 一个新的监管框架允许规避研究技术保护措施.
研究的目的:
- 为了使电影能够进行大规模的计算研究.
- 在电影数据集中测量性别和种族/民族代表性.
- 为了揭示好莱多样性的趋势.
主要方法:
- 数字化了2,307部电影 (票房最高和获奖提名,1980-2022年).
- 开发了一个使用计算机视觉进行演员识别的计算管道.
- 应用人类感知模型用于性别和种族/种族分类.
主要成果:
- 证实了过去十年来好莱电影的多样性增加.
- 揭露了有关代表性的临时分析结果.
- 证明了大规模数据驱动电影分析的可行性.
结论:
- 新的监管框架促进了计算式电影研究.
- 计算方法为电影表现提供了实质性的见解.
- 大规模的数据分析为了解媒体多样性提供了新的途径.
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