I have always been interested in the "physics of pop culture" and how we can analyze the culture that we love to consume every day with data science. To further explore this curiosity, I did a deep dive into Alisun Pawley and Daniel Mullensiefen's research on The Science of Singing Along for a quick Metis investigation presentation. The presentation deck and an overview of key concepts is included below and you can check out the full article here!
Back in 2011, a very popular TV show called Friday Night Lights was wrapping up it's final season. As with all shows that rally cult followings, fans cried out for a follow up movie; but this one was different. What this meant is that in it's lifetime as a story "Friday Night Lights" was a real life situation that inspired a book, which was turned into a movie, which became a TV show which could potentially become a movie again. This is when I personally became interested in the "cross section" of pop culture. I found myself thinking about questions like which shows are best suited to make the transition to the big screen? I decided to examine this question for Project Luther during weeks two and three @ Metis.
Week 1 @ Metis and our first project are in the books. Project benson (each project is cleverly named after a famous detective; the firsts' namesake being Oliva Benson of perennial NBC cop drama Law & Order: SVU) centered around using MTA turnstile data as a vehicle to explore python's data exploration capabilities and the iterative design process.
Hello World! This is my first blog post! Using this space to share data science projects, insights, thoughts and whimsy!