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Updated: Jan 22, 2026

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Quantifying X-Ray Fluorescence Data Using MAPS
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美国市场的亚马逊X射线的场景级电影数据与IMDbb相结合
Safal Shrestha1, Yeonie Heo1, Alexander T J Barron2
1New York University Abu Dhabi, Abu Dhabi, UAE.
Scientific data
|January 20, 2026
概括
这项研究引入了一个大规模的电影数据集,包含场景级别的细节和角色信息,克服了以前的剧本集对准确内容分析的局限性.
科学领域:
- 计算语言学 计算语言学
- 数字人文学科 数字人文学科
- 媒体研究 媒体研究
背景情况:
- 之前关于电影内容分析的研究受限于小型,不一致的剧本数据集.
- 现有的数据集通常使用剧本草稿,而不是最终的电影产品,影响准确性.
- 缺乏标准化的场景表示和演员元数据阻碍了大规模研究.
研究的目的:
- 呈现电影内容的结构化,场景级数据集,以进行增强的分析.
- 通过使用标准化和全面的数据源来克服先前研究的局限性.
- 促进电影作为文化文物的大规模定量研究.
主要方法:
- 从亚马逊X-Ray (美国亚马逊Prime Video) 编译了3,265部电影的场景细分.
- 每个场景的详细角色,将它们与IMDb ID联系起来.
- 包括3,110部电影的字幕和链接到IMDbID的标题,用于元数据增强.
主要成果:
- 创建了一个大规模的,结构化的电影场景级内容数据集.
- 数据集包括每个场景的角色存在和对话数据.
- 能够将电影数据链接到外部元数据源,如IMDb.
结论:
- 该数据集提高了电影数据分析的一致性和可访问性.
- 促进对屏幕表现和叙事结构的准确,大规模研究.
- 为电影内容的定量研究提供可靠的基础.
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