Last week was pretty busy, but in a good way. It was a combination of studying, preparing to pitch my project, and of course NYCDH Week (and a CUNY Library workshop, and an ITP workshop). I wasn’t able to attend in 2020, so this year I ended up overcompensating and RSVPing to as many workshops as I could. It was a lot of information and it ended up being a little overwhelming, but thank goodness I took notes and got some good ideas for the NYC Community Fridges Archive!

NYCDH Kickoff Event

I attended the second part of the event, the one with the Graduate Student Award Ceremony. I got to learn about so many interesting projects (all winners were from CUNY GC, yay!), but the one who impressed me the most was Daniel Fox’s “Is There Gender Bias in the Genre Labels for Musicians on Wikipedia?”. Gender Bias on Wikipedia is such an interesting topic, and I never considered it as far as music is concerned. Daniel used data analysis tools to research the genre labels associated with musicians and found out that yes, there are some differences in the way artists of different genders are treated.

Network Analysis for the Humanities

I have to admit, I was a little intimidated by the title of this workshop. Network analysis sounds like a very complicated topic, and my academic career is 100% in the Humanities. Fortunately, the instructor (Dr. Riva) kept the workshop simple enough that we could all intuitively understand what he was talking about. He uses Network Analysis to study the texts that are copied in different Medieval manuscripts: pretty cool if you ask me!

The workshop also included a hands-on part: first, we were divided into breakout rooms and asked to browse (https://moviegalaxies.com/): the website contains network graphs of the characters of several famous movies. I got to chat about Titanic, The Matrix, The Lord of the Rings, and more with students from all over the world (even Abu Dhabi!). I strongly recommend trying it: it makes it wayyy easier to understand movies with a lot of characters, like The Godfather! Dr. Riva also guided us in a tutorial to create a network graph on Gephi. It reminded me a little of Tableau, but more basic and less intuitive to use.

Collecting Twitter Data for Research

I was really excited about this workshop because I had seen some interesting text analysis projects based on Twitter Data during prof. Rhody’s class and I wanted to know how to use the Twitter API. Our instructor gave us a tutorial on how to use TAGS Explorer and RStudio Cloud to collect and analyze Twitter data. I was really impressed at how easy it was to use TAGS, but I got a little lost in the RStudio part…I’ll have to go back to the class materials and try that again. The fact that I was devouring a bunch of Indian food during the tutorial might have contributed to my getting lost.

Introduction to Omeka and Advanced Omeka

These are the workshops I was most interested in: Omeka is a fundamental component of my team’s project. Kimon Kiramidas guided us through the affordances of Omeka and the different kinds of projects one can create on the platform. In the advanced class, we learned how to use the plugins and themes, which are the way you can tailor Omeka to your project. I also got to ask a couple of questions I had about the NYC Community Fridges Archives: how can you collaborate in Omeka? What about accessibility? The instructor’s answers reassured me: 1) it’s super easy to collaborate on Omeka and you can establish different layers of participation 2) Accessibility is not necessarily built-in, but can be implemented with the use of Themes.