Author Archives: Matthew K. Gold

A few resources from the recent NEH Project Director’s Meeting

I recently attend an NEH Project Director’s meeting in DC and wanted to share news of a few projects that I thought might interest the group:

(in pre-release)


“MassMine is a social media mining and archiving application that simplifies the process of collecting and managing large amounts of data across multiple sources. It is designed with the researcher in mind, providing a flexible framework for tackling individualized research needs. MassMine is designed to run both on personal computers and dedicated servers/clusters. MassMine handles credential authorizations, data acquisition & archiving, as well as customized data export and analysis.”

Poemage: A Visualization Tool in Support of Close Reading

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“Poemage is a visualization system for exploring the sonic topology of a poem. We define sonic topology as the complex structures formed via the interaction of sonic patterns — words connected through some sonic or linguistic resemblance — across the space of the poem. Poemage was developed at the University of Utah as part of an ongoing, highly exploratory collaboration between data visualization experts and poets/poetry scholars. Additional details are provided in the companion paper [to appear in IEEE Transactions on Visualization and Computer Graphics].”

New DHDebates CFP is Up

We’ve been looking at various barometers of the field in recent weeks (conferences, blog postings, tweets, etc.), so I wanted to mention that Lauren Klein and I posted the Call for Papers for the 2017 edition of Debates in the Digital Humanities today. Some of you might be interested in looking through it to get a sense of the questions we’re asking and how they map to current concerns in the field.

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TACIT – A New Tool for Text Collection and Analysis

Thanks to Sava Saheli Singh, whose weekly round-up for the GC’s own Journal of Interactive Technology and Pedagogy brought a new tool to my attention: TACIT, Text Analysis, Collection and Interpretation Tool. From the website:

Though several limited-method tools for text analysis are already available (e.g. LIWC), and some have become part of standard statistical packages (e.g., SPSS Text Analytics), a unified, open-source architecture for gathering, managing and analyzing text does not exist.

The Computational Social Science Lab (CSSL) at the University of Southern California introduces TACIT: An Open-Source Text Analysis, Crawling and Interpretation Tool.
TACIT’s plugin architecture has three main components:

  • Crawling plugins, for automated text collection from online sources (e.g., US Senate and Supreme Court speech transcriptions, Twitter, Reddit)
  • Analysis plugins, including LIWC-type word count, topic modeling, sentiment analysis, clustering and classification.
  • Corpus management, for applying standard text preprocessing to prepare and store corpora.

TACIT’s open-source plugin platform allows the architecture to easily adapt with the rapid developments text analysis.

The tool is available on Github for those interested in checking it out. A related paper can be found on SSRN.

I have not used this tool, so if anyone here tries it out, please report back!

Data Project Posts from the 2014 Praxis Class

Hi All,

If you would like to see posts that students in last year’s Praxis course made in connection with the dataset assignment, please look at the posts tagged “dataset” and “data project.”

If you’d like to look through the blog as a whole (used in both the Fall and Spring semesters), please visit And here is the 2013-2014 class archive, which included a great series of lectures. Perhaps we can talk next week about the different shapes this class has taken over the three-year period of its existence. In the first year, we brought in many guest speakers, but in response to student feedback, we have curtailed that over the past two years.

Welcome to the Digital Praxis Seminar!

We’re excited to begin this new year of work in the digital praxis seminar. Please use the blog to post your thoughts as we work through our course readings. Share resources, link out to conversations, comment on compelling (or frustrating) passages in our readings. Above all, please post comments on the work of fellow classmates.