Artificial intelligence framework analyzes large comic book collections
Studying Comics at Scale with Artificial Intelligence: The PAGE Framework and Three Studies of American Comics and Japanese Manga
Artificial IntelligenceComputation and LanguageComputers and Society
Summary
Most comics from the 20th century haven’t been studied all together because they’re so large and varied. The authors created PAGE, a system that uses artificial intelligence to break down scanned comic pages into parts like panels and text, then describes what’s shown using a model that reads like a human would. They used PAGE on thousands of American comics and Japanese manga to study topics like how political power was shown, artistic styles, and who speaks in the stories. This approach could help make comic archives easier to search, support readers with vision problems, and preserve old comics.
What this means in practice
- •For digital archivists: Make large comic collections searchable by visual content and text using automated AI annotations.
- •For accessibility tool developers: Create aids for blind and low-vision readers by describing comic images automatically from scans.
Authors
Emilio Ferrara
Abstract
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 and genre. We demonstrate the framework on 3,929 American comic books (1938--1956) and 87 volumes of Japanese manga, in three studies, each resting on a different capability. The first pairs text search with visual reading to recover how a mass medium portrayed political power. The second measures the page's visual form across an industry and recovers the hand of individual artists. The third follows who speaks across two comics traditions, checked against human annotation. Beyond research, the same instruments can make archives searchable by what is drawn, open comics to blind and low-vision readers, and help preserve fragile collections and credit uncredited artists. We outline a research agenda in which artificial intelligence strengthens the study, preservation and reach of the medium.