Here's another pass at some more of the 9/11 Pager data that was released by Wikileaks this week. I did some work earlier that explains most of what I'm doing. This time, I tried to improve the visualization. I'm also using a directed graph of domain names that appear in the messages as they relate to the unique pager numbers.
I spent Thanskgiving and the day after relaxing in my own peculiar way--by mining the Wikileaks 9/11 pager data.
Here are some early results:
I started by pulling out all the email addresses from the pages and storing them in their own table, with keys to their original page. I also pulled the unique pager numbers from the pages. What I got was a bipartite directed graph with one side being emails and the other being pagers, with messages functioning as edges. Using Django, Graphviz, Cinelerra and a bunch of other tools, I was able to make a video of the graph as it lights up on each relevant page.
The first assignment for the class was to collect data from each other and analyze it. In the first round, each of fours groups polled their classmates and acquired enough data to investigate a question they posed about the class as a whole. The groups exchanged data with each other and created interfaces and visualizations.
Kunal, Michael, Vanessa:
I am teaching the JP Morgan Collaboration Studio, also known as Visualizing the Financial Space, along with Chuck Yust, Scott Pobiner, and Heico Wesselius. Chuck and I are leading the group in the Design and Technology department, where we're focusing on the interfaces and visualizations that can be created for JP Morgan's social network.
I just discovered a bevy of research on the Enron email dataset. After the collapse of the company, all of the email from the roughly 150 ex-employees made it into a publicly available archive. This is a pretty valuable resource for people looking to test data-visualization ideas for social relationships. Hopefully, Chuck and I can find a way to use this in the fall for the collaboration studio we're teaching.
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