Democracy Viewer
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Text Mining for Historical Analysis

Text Mining for Historical Analysis

Text Mining for Historical Analysis offers a critical intervention into the evolving field of digital history. It introduces "computational historical thinking"-a mode of thinking that explores the epistemological entanglements between computation, theory, and historical analysis, emphasizing how computational procedures actively shape the questions we ask and the meanings we derive from data. Through sustained engagement with historical corpora—such as the 19th-century Hansard debates and contemporary U.S. Congressional Records—this book demonstrates how to attend to both structure and semantics, thus reimagining the relationship between computation and historical knowledge in the digital age.

Beyond the Black Box: Toward Transparent AI for Computational Text Analysis in the Digital Humanities

Beyond the Black Box: Toward Transparent AI for Computational Text Analysis in the Digital Humanities

This article introduces Critical Generative Interpretation, a method that supports humanist inquiry by making AI-generated insights traceable and grounded in textual evidence. By linking large language model (LLM) outputs to structured knowledge graphs derived from source texts, the method enables scholars to critically assess where generated interpretations come from and how they relate to the original material. This methodology supports humanist inquiry through close reading. Through a case study of Harold and the Purple Crayon, the article shows how this approach fosters interpretive engagement and makes AI a method for humanistic knowledge production.

Foundations and Applications of Humanities Analytics

Foundations and Applications of Humanities Analytics

Computational methods allow researchers to systematically analyze and interpret large volumes of social, political, and cultural data, uncovering underlying patterns and insights at scale. These course materials, made for the Santa Fe Institute, are designed to equip humanities researchers with computational and quantitative tools. The course aims to foster a supportive community, build practical skills, and diversify the field of humanities analytics by welcoming participants from various backgrounds and stages of their academic careers.