Just today, I attended a Data Scraping with Python workshop, waltzed into an Advanced Excel workshop, and then took the trip over to a seminar on Heavy-tailed data with Rob Axtell.
That’s a regular Friday at George Mason University. For me, at least.
My days usually start with work as a Digital Scholarship center Graduate Research Assistant. As a part of my course, I attend an Introduction to Computational Social Sciences, a Scientific Databases, and a Numerical Methods class.
While my mind tries to contain myself, my heart cannot. It still blows my mind that I exist here, that I study these subjects, that I work on assignments, projects, and research papers, with these professors.
I am a total nerd about school, unashamedly so.
Before I dive headfirst into my heady obsession with my course work, here’s a summary of sorts on it: MS in Computational Sciences.
Here’s a quick overview on all I’ve been gushing about with anyone with ears half a kilometer from me:
- Hounded the Fenwick library for Digital Humanities related stuff. Bit my lip when I saw the library.gmu.edu link to Digital Humanities info-guide on my orientation slideshow.
- Saw a Hamilton poster in the Science and Technology Subject Librarian’s office and of course I had to go talk to her about US History and Digital Humanities.
- Contacted everyone in the Digital Scholarship center until they figured they might as well take me in. (Kidding, there was an interview where I fire-hosed the wonderful WM with my Digital Humanities enthusiasm, of course.)
- Pitched my goals as learning ALL the software in DiSc until my head fizzled back onto the firm ground and fixed on only the 7 or so Digital Humanities tools there are.
- Attended in-house GIS, Python, Tableau, etc workshops.
- Shadowed DK on her consultations with researchers for NVivo, R, and data services.
- Shadowed WM on her consultations with researchers on data searching, capturing, services, visualizations etc.
- Onto learning Gephi, Voyant, Atlas.ti, MaxQDA, NVivo, Omeka, Tableau, etc better.
- Onto figuring out a sensible info-guide for Twitter data mining.
- Talked to RRCHNM about DH projects and summer internships.
- Attended a talk on Text Mining with Digital Humanities tools like OpenRefine, R, and APIs with Laura Crossley, PhD student, Department of History and Art History, who, it turns out, leads the Digital Humanities Now. And what do I find out but my name in the Editors-at-large list. Surreal.
- Computational Social Sciences. Uh, where do I start? A course that combines critical thinking, human behavioral psychology, economics, political sciences, governance, some math, and loads of computational models. Have I ever truly loved writing an exam before? Each model blends so many topics together it actually spins my head, in a good way. Psst, there are loads of Doctor Who references in here.
- The possibilities! How do anti-vaxxers affect a population, how does climate change affect countries, how does a hurricane affect a city, how and where do physical and online ‘terrorist’ connections take place? We simulate that if we get the real time data, or randomize attributes for agents just to see what happens. The social experiment simulation I can get grades for.
- A Computational Social Science research paper and project about which I can only say my 2010 Facebook personality quizzing, Good Place TV show, philosophy podcast material, stranger behavior analyzing, self is practically bursting with excitement.
- The professor said to take your favourite theory and see how far it is applicable and I was planning on a model of fandoms in a comic con – How do book/movies/TV show recommendations travel in a group of people? The amount of information each agent carries can be randomized. For instance, Agent A with 80% love for Doctor Who, can interact with Agent B with 70% love for Percy Jackson and come away with some amount of interest for Percy Jackson as well, while Agent B walks off with more interest in Doctor Who. Maybe? Possibly? Thanks for the ideas at the very least Malcolm Gladwell.
- Consumed an MIT lecture series on Brains, Minds, and Machines in preparation for it.
- Realized IIT professors almost single-handedly helped me know of concepts in Numerical Methods from so far away and 3Blue1Brown made me understand them really. Why is Mathematics not taught like this more often?
- Attended a Computational Social Neuroscience Group (CSNG) to see the Computational Neuroscience projects in one of those increasingly frequent moments I Could Not Believe I was there for It.
- Obsessed over courses to take over the next few semesters because I want them all. What do you think?
- Scientific and Statistical Visualization CSI 703
- Agent-Based Modeling and Simulation CSS 610
- Cognitive Foundations of Computational Social Science CSS635
- Origins of Social Complexity CSS620
- Principles of Knowledge Mining CSI 777
- Computational Learning and Discovery CSI 873 / MATH 689
- There are so many more I want to be taking,
- CSI 501: Introduction to Scientific Programming,
- CSI 639: Ethics in Scientific Research
- CSI 754: Earth Science Data and Advanced Data Analysis
- CSI 758: Visualization and Modeling of Complex Systems
- CSI 773: Statistical Graphics and Data Exploration
- CSS 625: Complexity Theory in the Social Sciences
- CSS 630: Comparative Computational Social Science
- CSS 640: Human and Social Evolutionary Complexity
- CSS 692: Social Network Analysis
- Etc, etc, etc … In So many other departments too. But cloning hasn’t been invented yet and I ain’t no Hermione.
Suffice it to say, I am learning So, SO, sooo much. I will write further on NetLogo, Agent-based modeling, Computational Social Sciences readings, DiSc softwares, Harvardx’s Introduction to DH, Miriam Posner’s DH101, Internship possibilities for a DH person in and around DC, etc., etc., soon.
As part of my NaNoWriMo word count, I hereby in-formalize this academic blog.