I’ve been mathematically analyzing my Twitter feed to determine how best to position my tweets for maximum impact, and have been documenting the work on this blog. While I’ve not come to any brilliant conclusions yet, I’ve made progress. My first post on the subject described clustering my followers by their hashtag use to see […]

# networkx

## Bayesian network modeling stock price change

Taking a cue from the systems biology folks, I decided to model stock price change interactions using a dynamic Bayesian network. For this analysis I focused on the members of the Dow Jones Industrial Average (DJIA) that are listed on the New York Stock Exchange (NYSE). Bayesian Networks A Bayesian network is an acyclic directed […]

## 100th post to badass data science

This marks the 100th post to badass data science. I’ve written about everything from Lady Gaga to computational fluid dynamics, usually with a science or data related spin. I thought I’d look at my posts analytically rather than simply reminisce. First, here is a tag cloud for the first 99 posts: From this tag cloud, […]

## myers-briggs personality interaction map

After my last consulting gig for Yoyodyne Propulsion Systems (YPS), they invited me back to troubleshoot their R&D team’s group dynamics [1][2]. To get started, I administered a web-based Myers-Briggs Type Indicator (MBTI) assessment to each member of YPS’s R&D team to discern their personality types [3]. I then plotted the personality similarities between the individuals […]

## data scientist goes coolhunting…

Intuitive coolhunting scales poorly. Here’s some math to help fix that problem: Axioms of cool Five axioms enable us to mathematically model cool: No one is intrinsically cool, individuals simply channel it. Ability to temporarily hold coolness varies by individual. Coolness naturally flows into some individuals more readily than others. Rate of coolness flow into […]