R/iGraph Holiday network animation and How-to tips

Posted by on Dec 17, 2012 in Data Visualization, Information Visualization, Network Animation, R, r-project, Social Networks | 0 comments

largeframe_Peace_OpeningThe 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.

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How to: network animation with R and the iGraph package & Meaning in data viz

Posted by on Nov 27, 2012 in Data Visualization, Information Visualization, Network Animation, r-project, Research, Social Networks, Uncategorized | 11 comments

This article lists the steps I take to create a network animation in R, provides some example source code that you can copy and modify for your own work, and starts a discussion about programming and visualization as an interpretive approach in research. Before I start, take a look at this network animation created with R and the iGraph package. This animation is of a retweet network related to #BankTransferDay. Links (displayed as lines) are retweets, nodes (displayed as points) are user accounts. For each designated period of time (in this case, an hour), retweets are drawn and then fade out over 24 hours.

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Network vizualization and meaning shifting due to algorithm settings

Posted by on Nov 16, 2012 in Data Visualization, Information Visualization, Network Animation, r-project, Research, Social Networks | 0 comments

Partially processed network layout

Data visualizations are useful for exploratory work and as an aid in communicating findings. Data visualizations also seem to be in demand these days as a kind of eye candy for capturing attention. But when we look at one engaging enough to hold our attention, we want to know what it means. In other words, we want to interpret the image we see and try to extract meaning. The image on the right is the same OccupyOakland retweet network that I have used in other posts (and in the post below), but it looks different. Why?

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