Month: August 2018

Posted on

The Occasional Mentor: On Computing Resources in Digital Humanities

THE OCCASIONAL MENTOR
A monthly-ish column based on questions I’ve answered on Quora, heard on Slack groups, and other career advice I’ve given over the prior month. Hope you like it, but feel free to challenge me in the comments, if you have a different experience. Below are questions I answered in July.

What Should I Learn About Computer Science for Studying History with Digital Humanities

Answered on July 25, 2018

I recommend visiting HASTAC.org. It is a group of academics and practitioners working in digital humanities. There are resources including local events, national conferences, blog posts, discussion lists and trainings.

You can look for digital humanities institutes and departments at local universities to see if they offer public programming. Many do. Where I live in NYC, Columbia and CUNY Graduate Center offer public programs. CUNY has an open access social media platform for digital humanities. Their digital humanities resource guide is pretty comprehensive: CUNY Academic Commons Wiki Archive.

I’ve seen some pretty interesting uses of text analysis, 3D printing and modeling to analyze historic texts and artifacts. Researchers at Rutgers used 3D imagery to scan Roman coins that they 3D printed. The scans offered a finer representation of the relief than the naked eye can see and the 3D prints (similar to photocopies of paper documents) allowed people to hold and examine the object without damaging the original. When I was in the Digital Humanities program at Pratt Institute School of Information I made a presentation on digital tools for archaeology. We learned about a professor at Indiana University who recreated an Ancient Greek archaeology site in Second Life, complete with a toga wearing avatar of himself as a guide. (I’ll add links if I can find them).

Text analytics and statistical/rendering software (like R) can help examine documents by displaying frequency of terms or associating phrases. Researchers have used these tools to render social networks or do sentiment analysis, for example one could study court decisions or news articles to see how action and opinion related to a social or political topic changes over time. Some basic Python, JSON and statistics are helpful.