In an ideal world I would take pretty useful, but forced to choose between the two I'll take useful.
Here are two social graphs taken from my Twitter following data.
The first map, by TweetWheel, is pretty, has nice colors, a simple and elegant interface, and a nice circular layout.
But what does it really tell me? What knowledge do I gain by looking at it?
The second map, by InFlow, is not as sexy, uses less color, and produces some complex emergent patterns.
Yet, this second map gives me more information -- it shows me emergent patterns in the data [both graphs use the same following data]. Using arrowheads, the InFlow map shows me who is following whom within the community. This network layout shows the emergent communities of interest found in the data. It tells me I am not just following one theme here.
Both maps have my node and my link data excluded for ease of readability. From the second map I see that I have chosen to follow people in three emergent groups [the gray nodes are just satellites of the purple group].
By looking at who is in the group I can easily label them. The top group [ClevOH] are my colleagues in various economic development projects in Cleveland and NE Ohio. The middle group I labeled the Digerati. This is a dense group with most members following most others within the group. I see many redundant links here -- I could stop following several of these folks and probably not miss much -- since they are mostly following each other and probably aware of the same information. This group has a few satellites -- they connect to only one or two nodes in the group and therefore are not full members.
The bottom group is well connected to the Digerati, but they do have a clustering of their own. These are well known consultants in Knowledge Management, Social Networks, Organization Development and Management. Once the satellites on the right see this diagram, they may choose to follow the blue nodes on the bottom since they have much in common. Twitter networks evolve from people watching how others are connected, and then exploring the unknown person's tweets to see if they are worth following.
After viewing the last map, I have a new connecting strategy for myself on Twitter.
- need more diversity of info/topics/knowledge to monitor
- less Digerati, remove several redundant nodes
- more Consultants, more interaction with peers and elites in the consulting world
- few more local folks, but this cluster is pretty good
- look for conversations around electronic music, my hobby
- weave a cluster around social network analysis
- maybe add a little bit of randomness?
The first map is very easy and fun. The second map requires more work... but you get out what you put in!
What does your Twitter social graph tell you?