Project Videos

The best way understand digital humanities is to dive right in and see what digital humanists are doing. These videos describe the what/why/how/who of a broad swath of DH projects, with the goal of helping you learn what’s necessary to undertake similar endeavors.

The videos are inspired by Miriam Posner’s How Did They Make That blog post and video.

We are always accepting new videos, up to 10 minutes in length. Get in touch with Scott B. Weingart to contribute.

Archives, Museums & the Digital Humanities

Dominique Luster (Carnegie Museum of Art)

DH methods for public history museum projects.

History, Public History, Museums

Beyond the Ant Brotherhood

Tatyana Gershkovich (Carnegie Mellon University)

Dynamic digital archives of writings and timelines.

Literature, Modern Languages

Building your own data set

AmyJo Brown (War Streets Media)

A Journalist's approach


Civic Data Intermediaries

Bob Gradeck (University of Pittsburgh), WPRDC (University of Pittsburgh)

Open data and what can be done with it.

History, Social and Decision Sciences, Journalism

Data Visualization: Tableau

Emma Slayton (Carnegie Mellon University)

Data visualization with Tableau.

History, English, Modern Languages, Psychology


David Kaufer (Carnegie Mellon University)

Computer Support for Close Reading and Textual Analysis in DH.

Literature, Modern Languages, English

Finding the Klan with Network Analysis

Elaine Frantz (Kent State University)

Historical network analysis.

History, Network Science

GIS Mapping

Susan Grunewald (University of Pittsburgh)

GIS mapping with an emphasis on history projects.


Historical Gazetteers

Ruth Mostern (University of Pittsburgh)

Building historical gazetteers.


How to grow data forests with XML trees

Elisa Beshero-Bondar (University of Pittsburgh)

eXtensible Markup Language (XML).

Literature, English

Improving Access to Video Oral Histories

Michael Christel (Carnegie Mellon University)

Video oral history projects.

History, Public History

Logistic Regression

Matthew J. Lavin (University of Pittsburgh)

Machine learning for literary analysis.

Literature, English

Marriage & Divorce of Capitalism & Democracy

Simon DeDeo (Carnegie Mellon University)

DH methods for interdisciplinary studies and results.

History, Social and Decision Sciences

Measuring Art Historical Networks

Matthew Lincoln (Carnegie Mellon University)

Network analysis in the context of art history.

Art History, History, Network Science

Metadata Heatmaps for Distant Reading

Benjamin Miller (University of Pittsburgh)

Distant reading of a textual corpus.

English, Literature

Networks and Medieval Schoolbooks

Elizabeth Archibald (University of Pittsburgh)

Network analysis in the context of the history.

History, Network Science


Stephen Wittek (Carnegie Mellon University)

Building immersive VR projects.

English, Literature, LCS

Nico Slate (Carnegie Mellon University)

The online historical project

History, Public History

Structure-based Network Analysis

S.E. Hackney (University of Pittsburgh)

Structure-based network analysis.

Network Science

Stylometry and Authorship Analysis

Patrick Juola (Duquesne University)

Machine learning to identify authors.

Literature, LCS, English, History

The Historical TV Guide

Kathy M. Newman (Carnegie Mellon University), Steven Gotzler (Carnegie Mellon University)

Using digitized text to study television history.

English, LCS

The Latin American Comics Archive (LACA)

Felipe Gómez (Carnegie Mellon University)

Online archives in comic book markup language.

Modern Languages, Literature

Topic Modeling Subreddits

Chloe Perry (Carnegie Mellon University)

Computational techniques to topic model subreddits.

Psychology, Social and Decision Sciences