About this book:

"Chronicles and Code: Digital Methods for European Historians" serves as a comprehensive guide for researchers looking to integrate computational approaches into their study of European history. The book emphasizes that digital methods should always serve historical questions, not the other way around. It addresses the unique challenges and opportunities presented by European sources, such as multilingual corpora, historical spelling variations, and diverse archival practices. The introduction highlights the book's focus on transparency, rigor, and reproducibility, promoting a hands-on approach to turning vast historical records into analyzable evidence.

The book is structured into several thematic sections, beginning with foundational aspects like research design, corpus building, licensing, and ethical considerations. It then delves into technical workflows for digitizing sources, covering scanning, Optical Character Recognition (OCR), and Handwritten Text Recognition (HTR), followed by essential text cleaning and metadata management using standards like TEI, Dublin Core, and IIIF. These early chapters establish the critical importance of data quality and structured information as prerequisites for meaningful analysis, offering practical advice on managing the inherent messiness and uncertainty of historical data.

The core of the book explores various analytical methods, starting with exploratory text analysis techniques such as frequencies, collocations, and concordances, which help surface initial patterns in textual data. It progresses to more advanced Natural Language Processing (NLP) tools like part-of-speech tagging, named entity recognition (NER), and dependency parsing, enabling historians to extract structured information like names, places, and relationships. Subsequent chapters delve into thematic analysis with topic modeling, stylistic analysis with stylometry, and the quantification of sentiment, framing, and discourse. The book then shifts focus to spatial and relational analysis, detailing how to build social networks from prosopographical data, utilize Geographic Information Systems (GIS) for historical geography, and apply spatial analysis techniques like density mapping and spatial autocorrelation. Event modeling is also covered, emphasizing the representation of time and uncertainty in historical narratives.

The concluding chapters concentrate on the crucial aspects of data visualization, teaching principles for crafting effective static and interactive graphics in R and Python, and how to create web-based maps and dashboards. Finally, the book stresses the importance of reproducible research practices, including the use of notebooks, version control, and modular pipelines, along with strategies for packaging, sharing, and ensuring the long-term impact and sustainability of digital projects under the FAIR data principles. Through practical case studies from European history, the book demonstrates how these diverse digital methods can be integrated to address complex historical questions, transforming traditional scholarship with computational scale and precision.

What You'll Find Inside:

• A practical guide to digital methods for historians, covering text analysis (OCR, NLP, topic modeling), GIS (geocoding, spatial analysis, mapping), and network analysis (prosopography, centrality, communities).
• Emphasizes research design, data curation, and ethics, with specific attention to the challenges of European sources like multilingualism, historical spelling, and moving borders.
• Provides step-by-step workflows for transforming raw sources into analyzable corpora, from digitization and OCR/HTR to text cleaning, preprocessing, and the use of standards like TEI, Dublin Core, and IIIF.
• Focuses on reproducible research practices, teaching readers to use notebooks (Jupyter/R Markdown), version control (Git), and FAIR data principles to ensure their work is transparent, shareable, and sustainable.
• Features case studies from European history that demonstrate how to combine and integrate textual, spatial, and network analyses to answer complex historical questions.

Who's It For:

This book is designed for graduate students, academic researchers, and cultural heritage professionals working in European history. It is ideal for those who have historical questions rooted in rich archival sources but want to learn how to complement traditional close reading with computational methods. The text assumes no prior programming experience, making it accessible to historians who are beginning their journey into digital scholarship and want a hands-on, practical guide to building, analyzing, and sharing digital projects.