Welcome to the
Journal of Digital Humanities
Vol. 2, No. 1 Winter 2012

The Journal of Digital Humanities is a comprehensive, peer-reviewed, open access journal that features the best scholarship, tools, and conversations produced by the digital humanities community in the previous quarter.

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Introductions

Pacing Scholarly Conversations

The Editors

The advancement of scholarship relies on the timely communication of questions, methods, results, and reflections. The iterative publications Digital Humanities Now and the Journal of Digital Humanities are intended to facilitate this process. DHNow surfaces and distributes the conversations weekly in order to invite participation and feedback. The Journal of Digital Humanities then identifies the […]

The Digital Humanities Contribution to Topic Modeling

Scott B. Weingart and Elijah Meeks

Topic modeling could stand in as a synecdoche of digital humanities. It is distant reading in the most pure sense: focused on corpora and not individual texts, treating the works themselves as unceremonious “buckets of words,” and providing seductive but obscure results in the forms of easily interpreted (and manipulated) “topics.” In its most commonly […]

"A model of texts, built with a particular theory in mind, cannot provide evidence for the theory." David M. Blei

Some of the topics found by analyzing 1.8 million articles from the New York Times

Some of the topics found by analyzing 1.8 million articles from the New York Times

Clusters of voyages in the Maury Collection generated by a simple k-means algorithm

Clusters of voyages in the Maury Collection generated by a simple k-means algorithm

"The strictly linguistic character of this technique is a limitation as well as a strength." Ted Underwood and Andrew Goldstone

"For historians, literary scholars, and other humanities researchers, MALLET is a valuable addition to your toolkit." Ian Milligan and Shawn Graham

The results of a topic model, showing 25 topics found across a database of nearly 15,000 song lyric files.

The results of a topic model, showing 25 topics found across a database of nearly 15,000 song lyric files.

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ISSN 2165-6673