The MakeR way: Using R to reify social media data via 3d printing

Posted by on Oct 3, 2013 in Data Visualization, Information Visualization, Methods, Modeling, R, r-project, Social Networks, Uncategorized | 6 comments

small_3dprintIf you’ve read any of my previous posts you know that I am constantly experimenting with different ways to represent and explore social network data with R. For example, in previous posts I’ve written about sonification of tweet data, animation of dynamic twitter networks, and various ways to plot social networks (here and here). In each case the underlying idea is finding different ways to explore data under the assumption that sometimes just looking at something from a different point of view reveals something novel. In this post I will briefly discuss how to go from data to 3D model network, to 3D object using R most of the way.

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Data sonification with R: the sound of Twitter data

Posted by on May 29, 2013 in R, r-project, Social Networks | 2 comments

tweet_waveWhat does a tweet sound like? Not the kind that flies around in the air, but the kind that zips to and from our mobile devices. I’m intensely interested in finding ways to make sense of data. Sonification of data – representing data with sound – offers one way to do that. This post steps through R code to take the text of tweets and turn them into short chirping sounds. It also uses different tones for different users so that each user has a “voice”. In other words, this post shows how to use R to make Twitter data sing.

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46th HICSS Workshop

Posted by on Feb 8, 2013 in Ethics, Methods, Research, Workshop | 0 comments





The name itself evokes images of tropical sun, warm waters, surfing, and relaxation.

So what are the people in this image doing inside, intent on looking at computer screens? Instead of savoring the sunshine and walking on the sand, here they sit.  Inside.  Hunched over laptops.  Interpreting a series of instructions to make sense of social media data.  Listening to the SoMe Lab team explain what they are seeing.  They are not behaving as you imagine Hawaiian visitors would behave.

These dedicated researchers are taking part in the workshop organized by the SoMe Lab team at HICSS46, held this past January in Wailea on Maui. As a part of the workshop, they were hearing from the SoMe team about lessons the team has learned in the past fifteen months.

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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 | 13 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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