Paper Machines is an open-source extension for Zotero, which is a program that allows users to create bibliographies and build large text corpuses in an online database. Paper Machines enables Zotero to do text analysis and visualization aimed at researchers across a variety of disciplines in the humanities and social sciences.

Jo Guldi and Chris Johnson-Roberson invented Paper Machines to make state-of-the-art text mining accessible to scholars who lack extensive technical knowledge or immense computational resources. To this end, Paper Machines allows researchers to easily combine data sources—including JSTOR Data For Research and the user’s own corpus of texts—with the latest data-mining techniques. These include:

• geoparsing
• topic modeling
• word clouds
• phrase nets

The results of these processes can then be translated into a variety of categorical, chronological, and geographical visualizations to show the distinctive features of textual corpora.

Applying Paper Machines to text corpora allows scholars to accumulate hypotheses about longue-durée patterns in the influence of ideas, individuals, and professional cohorts. By measuring trends, ideas, and institutions against each other over time using Paper Machines, scholars can take on a much larger scale of texts than they normally do.

With Paper Machines, scholars can create visual representations of a multitude of patterns within a text corpus using a simple, easy-to-use graphical interface.