Reconstructing Peirce's Trails of Thought: Multimodal Computational Analysis of Non-Linear Manuscript Composition

Abstract

The digitization of manuscript collections opens new possibilities for analyzing complex, multimodal documents. Charles S. Peirce’s manuscripts at Harvard’s Houghton Library are a paradigmatic case, combining prose, logical notation, and diagrams, with frequent rewriting and backtracking across hundreds of pages. In the 1980s a manual reconstruction mapped the compositional topology of one such manuscript, later named an S-diagram. This study investigates whether computational methodologies can recover this compositional structure and if a reconstruction accounting for both textual and visual content confirms and extends the original manual effort. Our pipeline applies lexical and semantic similarity analyses to the text, combining them with a visual classification of each page produced by Vision-Language Models (VLMs). Integrating these approaches is essential to capture what we term semiotic continuity, which refers to the seamless integration of prose, notation, and diagrams within the same page. We validate the method against a formalization of the manual reconstruction, archival sheet variants, cross-manuscript links, and the convergence of the two similarity methods. The workflow reproduces the manual mapping in its annotated zone and extends it into regions the original did not cover. Ultimately, this framework can be applied to any manuscript collection characterized by extensive rewriting and multimodal composition.