Sugiyama algorithm of chat room interactions

We have been playing with the social network analysis (SNA) tool NodeXL this week as part of the Learning and Knowledge Analytics 2011 course.  NodeXL is a plug in for Excel 2007/2010 which allows you to visualize networks of interactions.  I have to say, it is a pretty neat tool!  We have produced some awesome visualizations, many which didn’t make a whole lot of sense, but certainly looked beautiful to the eye.  NodeXL has a Flickr gallery, if you want to see what it is capable of.

The one visualization we were able to make some sense of included here was an analysis of chat room discussions from our learning management system.  The chat room dialog contains mostly course related discussion which occurred online throughout a year course.  We managed to assign roles to chatters so that we could see where a student, lecturer, librarian or other support staff was discussing.  This particular graph uses the Sugiyama algorithm  to layout the nodes.  We did quite a bit of further layout work to color code the roles, organize the days, and get it looking somewhat logical.

In the diagram above the green diamonds along the top represent support staff intervening in the chat room.  The blue dots at the bottom are individual students.  The orange boxes represent days when chats tool place.  Finally the lines, which include the text of the chat feed from the person speaking them connected to the day they were uttered.  The text is not meant to be read but just adds to the complexity and visual appeal.  In NodeXL one can zoom in quite closely and highlight different aspects of the graph, so one could highlight a day and read all of the interactions occurring.

So what can we see here? Well students have a lot of chat utterances, and support staff are participating, some more than others.  Much of the chat seems focused on the latter part of the semester (the days are sequential from left to right).  Unfortunately, those who do not chat are not represented on our visualization, so we can not identify disconnected students.  It is a nice visual overview of an online social interaction.

One would have to code all of the chat utterances to fully understand what took place and perhaps produce a more telling visualization.  We have not done any coding of the semantic meaning of these utterances.  Perhaps that is our next project!

Visualizing Online Social Interactions

CC BY 4.0 Visualizing Online Social Interactions by Michael Paskevicius is licensed under a Creative Commons Attribution 4.0 International License.

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