Key Methods

WE1S uses digital humanities methods to conduct its research on large numbers of media and other documents mentioning the humanities. These “DH” methods in turn draw on computer science, information science, machine learning, text analysis, visualization, and other methods mentioned in our Bibliography. We’ve created explanation “cards” in plain language for many of these methods, each of which includes links to further information. (See our Methods card M-1 on “cards” as an explainability practice.) Some cards also point out important issues and limitations with methods.

Methods cards can accompany cards explaining collections and models, key findings, and software and tools as input components of WE1S Research-to-Action Toolkits, whose output components include Call-to-Action and Call-to-Communication recommendations.


Technical and Interpretive Methods

The cards below briefly describe some of the WE1S project's main methods for collecting, analyzing, interpreting, and reporting on its research materials.

Methods Issues & Limitations

As with any methods for exploring and understanding large datasets of material, WE1S methods at once enable new kinds of research and impose constraints on what can be done. The following provide a few key considerations that our team members (and, we hope, outside readers) take into account when analyzing what our methods tell us about our data.