Cross-Cultural Analytics is a research initiative led by Professor Stuart M. McManus (Department of History, The Chinese University of Hong Kong). The project is funded by the 2025/26 RGC Collaborative Research Fund – Young Collaborative Research Grant (YCRG) and aims to establish Hong Kong as a leading global centre for computational cultural analysis.
This project examines how Chinese culture influenced Europe and the Americas between 1550 and 1900, using methods that bring together data science and the humanities. We integrate:
- Large Language Models (LLMs)
- Knowledge Graphs
- Big Data analytics
- Rare book digitisation
- Computational philology
- Intertextual modelling
Our goal is to build new digital infrastructure for studying long-range cultural exchange and to support the future development of a permanent Cross-Cultural Analytics research centre at CUHK.
This repository hosts materials related to the Cross-Cultural Analytics project, including:
- Data schemas and sample corpora
- NLP pipelines and reproducible workflows
- Tools for text alignment, multilingual OCR, and semantic search
- Knowledge Graph construction scripts
- Experimental notebooks using LLMs for historical text analysis
- Documentation for collaborative research and student training
The project aims to:
- Build a high-quality textual corpus from CUHK’s rare book collections and public-domain sources.
- Apply LLMs and knowledge graphs to track the movement of Chinese ideas across continents.
- Model cross-cultural influence using intertextual, semantic, and citation analysis.
- Support new historical questions that cannot be answered through traditional close reading alone.
- Train students and researchers in responsible, methodologically rigorous digital humanities.
Stuart M. McManus is Associate Professor of History at CUHK and Associate Director of the Centre for Comparative and Public History. He works on the global Renaissance, classical scholarship, Chinese humanities, and the application of digital tools to historical research. He is also a recipient of major international prizes and grants, including the Dan David Prize.
If you use or fork this repository, please cite the Cross-Cultural Analytics project accordingly.