Text Mining for Historical Analysis
Books Hansard Congress R Digital Humanities

Text Mining for Historical Analysis

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Democracy Viewer

Democracy Viewer

Democracy Viewer is an open-source text mining application that enables analysts to explore and interpret humanities texts using techniques like word counts, TF-IDF, and word embeddings. It supports both distant and close reading. Analysts can upload their own datasets or work with curated collections available on the platform. Democracy Viewer also provides access to open government data, including U.S. Congressional records, making public texts more accessible for research and civic engagement.

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.