Cross-Cultural Analytics from the Ground Up: Building a Machine-Readable Corpus of Early China-Western Encounters

How can we create reliable machine-readable sources for studying the global history of print? This paper presents our preliminary work on a project entitled ‘Cross-Cultural Analytics: Using Big Data, Large Language Models, Knowledge Graphs and Rare Books to Chart the Influence of Chinese Culture in the West’. Studying European-language texts on Chinese culture and its reception in the West, from the sixteenth to the nineteenth centuries, faces a basic obstacle: no corpus exists that is both relevant to this question and structured with the standardized, machine-readable metadata that computational analysis requires. This paper presents a pipeline built to close that gap.

The initial corpus draws primarily on public digital repositories, especially HathiTrust, Internet Archive, EBBO, ECCO, Gallica, focusing on those texts in early modern intellectual and imperial lingua francas (e.g. Latin, Spanish, French, and English). We have developed a workflow for retrieving bibliographic records, filtering material by date and language, identifying duplicate records and converting heterogeneous source files into a consistent structure. Each text is linked to bibliographic metadata, including title, author, language, date, source and repository identifiers. This creates a foundation for later semantic search and intertextual analysis.

OCR quality remains a major obstacle, particularly in older books with variable typefaces, damaged pages or inconsistent spelling. We have therefore established a correction process that combines rules-based and LLM-based methods with targeted scholarly review. Our experiments with LLM-assisted correction indicate considerable promise, but they also show the need to carefully optimize prompts, chunk lengths and other parameters. We discuss how an appropriate balance can be found between improving readability and preserving evidence about the printed page.

By concentrating on corpus creation and OCR correction, this paper argues that the pre-print past becomes machine-readable only as the result of significant human thought and labour. Without this laborious initial stage, later analytical work of the sort prized in the humanities is impossible.