There have been a lot of utilities developed to help us understand who may be influential or what conversations are dominating in the social web. From the dawn of BlogPulse to a hundred (I presume) utilities born from the Twitter API.
Some are helpful. Some just make cool graphs. Some are broken. Many use their own criteria for ranking or evaluating data. This requires us all to accept a new lexicon to get much out of the the results. Some day soon, I will make a project of recording all of the most common definitions for "influence" from the various tools we use, the academics and pundits and our own strategy team.
Twinfluence
Beyond the information that Twinfluence displays, their second biggest asset is the clear and open description of what they are doing to crunch the data from 146,636 twitterers. They report our against Reach, Velocity and Social Capital.
Reach is pretty straightforward. Thye count followers and estimate second level followers of those. For my Twitter handle - jbell99 - my rank is #11,473 (92%). That means that out of 146K I am 11k on the list. I rank 92% higher than others in the collection.
Velocity groups similar twitters together so you are not comparing me to Samantha Ronson with her 830K followers. Overall, it is trying to indicate how fast someone is picking up followers. Depending on what you are trying to learn, I would argue this may not be that highly relevant. So long as a twitterer continues to add followers at even a low rate, depending on their reach, of course, they can be highly influential in their field.
Social Capital is the least useful of the measures. As Twinfluence puts it: "..It's essentially a measure of how influential are a twitterer's followers. A high value indicates that most of that Twitterer's followers have a lot of followers themselves...as twitterers build their follower network, their social capital tends to start very high, build for a while, then slowly decrease. This is probably because as most people start tweeting, they follow a few high-profile twitterers who may reciprocate. Over time, however, they attract more and more people - and that means more and more people with few followers, including bots, spammers, and silent followers."
So, social capital as they label it tends to follow a fairly predictive path for most users.
Twinfluence on ManyEyes
Now take the data from Twinflunce and jam it donw the pipes of IBM's Many Eyes, a visualization utility that displays cool Java interactives of different data.
Here is a display of Science "Tweeps" data from April and June that allows you to click inside the display to get detail and toggle settings to understand the growth rate differential between some of the Tweeps - Treehugger doubles their followers while RichardWiseman goes from 1100 followers to 7,700 by June.
The ManyEyes display is interesting yet remains a static snapshot of that April and June timeperiod. The IBM (client) platform is a neat way to make data more meaningful. Now if we were to idenify collections along the lines of Ogilvy's segmented influencers (e.g. design geeks, Mom-twitterers, etc...) and take monthly or even quarterly snapshots like what 2020Science did here, we might have an interesting and useful display.
Recommendation: Add Twinfluence to your DIY dashboard mapping influence and use the Reach and even Velocity numbers to help inform your effort (Social Capital shoudl be renamed and even then it's true value is not clear)
Try importing data into Many Eyes, you may be surprised.
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