I’m not likely to build this, but since I’m getting a fair amount of Twitter-related traffic these days, I’ll put it out there and hope that this idea intrigues someone else.
If we accept that Twitter is in large part a social technology, then we’re presented with a universe of questions about Twitter’s social character. At the most basic level, Twitter’s relationships can be either one way (I follow you) or two way (we both follow each other). One could look at a user to see what percentage of their relationships are mutual follows, but that doesn’t really interest me much, since I suspect there’s a lot of “oh, I guess I should follow them back” noise in there.
Where it gets interesting to me is when groups are exposed: not just you and me following one another, but you, me, and Dr. X all following each other. A mutual follow might just be someone’s Twitter etiquette (Twittiquette?) exposed, but a set of mutual follow relationships seems a more reliable indicator of substantive relationships.
Definition of a Twitter Set
A Twitter Set is a group of three or more Twitter users such that every member of the set follows every other member, and no other members exist for the set. Note that set members need not only follow one another. Also note that I’m leaving the question of whether @Scobleizer and @JasonCalacanis should count for this metric as an exercise for the student.
Why Track This?
I’m not sure. For me, I’m interested in tracking it (or rather, having someone else track it) for pretty much the only reason I ever do anything: it seems like there could be something interesting there; I don’t know what, exactly, but something interesting.
As a starting point, one could build some fascinating visualizations off of this data: seeing where sets exist, how big they are, and how they overlap would be fascinating. How many sets do users tend to belong to? What’s the largest set that exists on Twitter, and who’s in it? How are sets distributed across the universe of Twitter users? Really nice visualization fodder.
More Details, Please
I think you could also reduce this to an interesting metric that shows something (again, I’m not sure exactly what) about how different people qw( use establish expose ) relationships on Twitter. If we say that a user who is part of a single, closed set (i.e. all set members follow only one another) should have a value of one as a baseline, we could use something like this:
A = Total number of sets within the user’s Twitter relationships
B = Number of people that the user is following
C = Size of largest set within the user’s Twitter relationships
User’s Twitter Set Value = (A / B) * C
Since the number of people that the user is following still seems relevant, I’m inclined to explicitly include the following count in the expressed metric, like so:
If you and your four closest friends only follow one another, the “twitter set value” for each of you would be…
(1 / 5) * 5 = 1
…and I’d express that as Twitter Set Value (TSV) = 1(5)
My own case (eyeball estimate, haven’t checked real stats) would be something like:
(8 / 84) * 4 = 0.38
TSV = 0.38(84)
Again, I’m not sure exactly what it would mean, but I’d be really interested in seeing this in action…any takers?