Making Sense Out of Online Social Network Data

Marc Smith

Marc Smith addressed a widespread problem with archived data in social networks:  how do you make sense out of the very large collections that are available?  We live in a world of machine-readable networks, and we need to have a browser for them.  Crowds gather in networks and are important; network sizes and shapes are relevant questions.  Many personal archives collect content but not the connections that link them; for example, they may collect tweets but not the followers.  We need to reassemble the crowd that has gathered around every interest.  Archiving the content is not difficult, but archiving the connections is, and few of the resellers of social media do so.

Smith suggested the NodeXL system as one which provides a good overview to generate and visualize network structures.  (See my earlier post on Ben Shneiderman’s Miles Conrad Lecture at the NFAIS meeting for more on NodeXL.)  Here is an example of a network generated by NodeXL.  It shows connections by people tweeting about Rep. Michele Bachmann on January 25, 2011.

A crowd has structure and shape and can be mapped, as the above chart shows.  Each person can form a tie between others, and when those ties are aggregated, a picture emerges.  Its creators envision a hundreds of NodeXL data collectors around the world collectively generating a free and open archive of social media network snapshots on a wide variety of subjects.  Smith therefore encouraged users to download NodeXL (it’s free) and run it on topics of interest to them.

Don Hawkins
Columnist, Information Today and Conference Circuit Blog Editor


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