Tomorrow, I’ll be making a return visit to the high school where I spent a decade in the mathematics department as a teacher. I’ve got the chance to speak to ten classes over the course of six class periods and tell them a little bit about what I do as a data scientist. Since many of the students will be familiar with concepts like vectors and trigonometry, I’ve decided to do an activity involving the Python gensim package and Word2Vec.
In a couple of earlier posts, I showed an example of a social graph created from Twitter data and Plotly, a graph of relationships between educational technology enthusiasts on Twitter. Those posts were more for the educator audience that I write for, but increasingly, I’m getting feedback on my posts from other data scientists, so I’ve decided to include my code, both here on this blog and at my Github account.
In a recent post, I displayed the social network graph that I created using the Twitter API and Plotly. There are a number of interesting applications here. Given my history with education, one that I think that shouldn’t be overlooked is as an interesting way to teach graph theory for an innovative teacher and school. I taught graph theory myself for several years as part of a discrete mathematics course. While the textbook I used included many examples of “real world” problems that I found engaging, the students didn’t always agree.
Using the Twitter API and Plotly with Python, I created a visualization of a recent #EdTechChat on Twitter, held on December 14. If you aren’t familiar with graph theory, the dots in this visualization are referred to as nodes or vertices. They represent the Twitter users that participated in the chat. The line segments connecting them are called edges and represent a relationship between two Twitter users: one user follows the other.