Robert Mason, Shawn Walker and Jeff Hemsley participated in the University of Washington, Information School’s iAffiliates Day, “an event that fosters new partnerships and showcases the innovative work being done at the iSchool. The event is an unconference format with the theme of discovering information partnerships”. Participants give a two minute lightning talk intended to “enlighten, inspire, educate, or otherwise engage the audience” about a given topic. Jeff chose to “otherwise engage” the audience with a two minute rap about data visualization. Read more for the full text.Read More
As a researcher interested in information flows in digital environments I’m often interested in finding patterns in social trace data. For this discussion we can think of digital social trace data as the text that people post into threaded topics on forums, like on Reddit or a Wiki Talk page on Wikipedia. One way to find patterns in this kind of data is to make visualizations based on different quantifiable dimensions in the data, for example, total topic volume per day, volume per thread per day, and, possibly, the intensity of the discussion (as interpreted by qualitative researchers). In the remainder of this post I will note what we can learn from our visualization as well as its limitations and then post the R code I used to make the plot.Read More
Gaston Sanchez’s post on R-Bloggers inspired me to waste a bit of time. He wanted to replicate the Google Charts widget to make gauges. I modified his code (below) in some minor ways and made a function out of it so you can alter the look and feel of your gauge. Feel free to pilfer and modify the R code…
A couple of weeks ago Bob wrote about a post about a research note that was recently accepted to the iConference. In it we outline the beginnings of a research project where we look at the interaction of different media platforms (Twitter and Blogs) with more traditional sources. In this post I go through the R code we used to plot, and visually compare, the volume of different information sources.
The data for this example is randomly drawn along a Pareto distribution so anyone should be able to just open the file, run it and have plots. Like I did in the last R example, I have used comments in the code to explain what I’m doing in the creation of these plots. After the code I give a brief introduction on the tool I use to select colors.Read More
The animation embedded in this post was done using R and the iGraph package and was, frankly, a great deal more work than I thought it would be when I started. What kept me going was a desire to express a wish for the New Year while also experimenting with some functionality that might be useful in my future research. In the following post I will provide some example code that extends my previous attempts at network animation by: 1) using the iGraph plot parameter margin to zoom in and out of different parts of the graph; 2) use the neighborhood function to highlight an information spread; and, 3) moving nodes along a path where you know the first and last point and the number of steps you want to make between them. I can imagine using the first two in my research, and the third was, well, just fun. I’m a geek. I’ll end the post with a line or two more about my motivations for creating this particular animation.Read More