Journal: Why am I Journaling?

I’m taking “Preparing the Future Professoriate” this semester at Virginia Tech, which is one of the core classes for the “Future Professoriate Certificate”. The class has us writing blog posts along with weekly journals. Since I’m now transitioning into the phase in my doctoral program where I need to transition into writing papers, just getting in to the habit of writing more can’t hurt. Let’s work on just writing more, then focus on tailoring my voice towards different audiences.

I wrote a blog post and gave a seminar talk about the Watts 2002 paper. The next step is thinking about expanding the binary decisions with externalities model to a psychological plausible decisions with externalities model. This has been the goal of the multi-agent neural-network (MANN) project. Context from the Watts model From an information diffusion perspective, a cascade is the spread of information from an initial set (seed) of individuals (nodes).

A Simple Model of Global Cascades on Random Networks

Duncan J Watts wrote a paper that was published in 2002 titled “A simple model of global cascades on random networks” in the Proceedings of the National Academy of Sciences (PNAS). It’s a seminal paper in my current work on information diffusion in (social) networks. Watts shows how the interactions between local dependencies, fractional threshold, and heterogeneity relate to information cascades in networks. My work builds on these ideas, so it’s important to have a strong understanding of the terms and model specifications outlined in the paper.

Scientific ‘Purity’ in the ‘Connected Age’

I just started reading Six Degrees: The Science of a Connected Age by Duncan J. Watts. It’s a book on network theory and related to the Multi-Agent Neural Network project I’ve been working on. The first chapter, “The Connected Age”, reminded me of this XKCD comic: When first saw the comic as an Psychology / Neuroscience undergrad, I found it extremely amusing – I wasn’t on the bottom! To my delight, the book chapter further highlights the need for “less pure” disciplines.

SWC: Software Carpentry as a University Course

https://software-carpentry.org/blog/2016/02/swc-as-a-university-course.html

SWC: Teaching Bimodal Workshops with a Large Range

https://software-carpentry.org/blog/2015/11/teaching-extreme-ranges.html

SWC: Assessing Our Learners Part I

https://software-carpentry.org/blog/2015/06/learner-assessment-part-01.html

Getting Started with Data Science and Analysis

I’ve been an instructor for Software-Carpentry (SWC) over a year now. It’s been a facinating experience and I’m proud to be a part of an open source movement promoting best practices. Typically when looking to start learing data science/analysis the first things people look up is something along the lines of: “learn python”, “free online r course”, “data science python”, “r jobs”, etc. Or scan through the coursera offerings. I’m a bit biased, but I think the SWC material is one of the best ways to just get familiar with the basics.

SWC: Cookie Cutter

https://software-carpentry.org/blog/2015/02/cookie-cutter.html