Studying Comics at Scale with Artificial Intelligence: The PAGE Framework and Three Studies of American Comics and Japanese Manga· 用 AI 研究大规模漫画：PAGE 框架及案例
Comics are one of the great visual records of the twentieth century: hundreds of thousands of pages in which a mass readership saw its leaders, its wars and its heroes. Most of this record has never been studied as a whole; comics scholarship proceeds one book at a time. We argue that artificial intelligence, including generative models, can change this to the benefit of the medium itself. We propose PAGE, a framework that makes artificial intelligence an instrument for comics research. It parses every scan into panels, text and a bibliographic record; annotates each page with a vision-language model that follows a written codebook, as a human coder would; grounds samples of these readings in human annotation; and explains change across an archive, with estimates controlled for publisher a
使用 AI 框架 PAGE 研究美日漫画。
- 核心方法
- 开发了 PAGE 框架，通过图像语言模型解析漫画扫描，自动标注页面内容，并结合人工标注验证模型准确性。
- 适合谁读
- 研究者、漫画爱好者
- 要解决的问题
- 传统漫画研究方法难以对大规模漫画资料进行全面分析。
- 关键实验
- 案例研究包括美日漫画的出版变化、视觉叙述技巧的演变等，具体数据未详述。
- 主要贡献
- 提供了大规模漫画研究的新工具，能够跨档案解释漫画的变化趋势。
- 意义与局限
- 为漫画研究带来了新的视角和技术手段，但可能存在对出版商影响的控制不足的问题。