Every so often there’s a new metric ranking, a way of measuring the power of social media. Now there’s one for Twitter, the Tweeterboard. The Tweeterboard measures "who is influential on Twitter based on their conversations with other Twitter users." Unfortunately, research last week reveal the system can be easily gamed with "@bait."
The core metric of the Tweeterboard remains @s, both given and received. Officially, score is calculated "using some algorithmic mojo that resembles the link analysis algorithms used by search engines." But @s heavily weigh the score , and it’s better to receive than it is to give. Giving in comparison to receiving creates a negative box score.
Which leads to @bait. By writing highly provocative tweets, users can bait fellow tweeters into conversation. Responding to some, but not all or mass replying with a singular tweet creates positive equity for your box score.
Last week, I openly tweeted my @bait experiment and threw out Tweets comparing a would-be Green Bay Packers vs. the New England Patriots Super Bowl to a battle between Rocky vs Darth Vader. The @s flew and sure enough, I shot up to the top ten on the Tweeterboard. Compatriot in crime Doug Haslam made it to #3!
With no written metric, it’s hard to determine what exactly makes the Tweeterboard tick. In a more drastic example, Adele McAlear noticed a new Twitterer, bugman1984, who shot to the top of Tweeterboard with less than 30 followers.
Like many other so called rankings, it’s game-able, and subjected to the biases of the algorithm creator. Rankings are always great ways to find new Twitterers and blogs to follow, but they vary in accuracy. One key barometer to look for is multiple variables, with more variables countering individual metric weight, hopefully making for a more balanced, composite picture. I also prefer rankings that do not have a subjective, human determined content ranking.
It’s important to note that the most important ranking is that of relationships. Only a person or business can truly determine the weight and power of those relationships. Whether it’s love, revenue, inaugural ball invites, etc., relationships build results. See K.D. Paine’s new book on measurement for more.
Other Twitter Members Weigh In
It seemed appropriate to ask other Twitterers what they thought of the Tweeterboard. Here are their answers:
Connie Reece: Tweeterboard: Not sure if legitimate is correct word. Do not think it adds real value because of way it is designed. Looks at too few ppl to be statistically significant; you lose pts. for conversation w/ ppl whose updates are protected. Tweeterboard is also link aggregator — pulling in blog content to the site from ppl on Tweeterboard. I do think Tweeterboard COULD have value if it awarded pts. for reciprocity rather than popularity.
Dave Fleet: Tweeterboard encourages twitterbait – ask questions, get @ replies, leap up the board. Rewards taking, not giving.
Mack Collier: Can see little value to Tweeterboard other than seeing who to follow, and ego-stroking for those on list
Adele McAlear: I’m suspicious of it’s number crunching reliability. Methinks buggy performance.
Tim Walker: "Legitimate"? I don’t know. Impossible to understand relation of inputs to output? Oh, yes. Should be more intuitive, sez I.
Roy Blumenthal: To my mind, tweeterboard isn’t an ‘analytic’. It’s a vanity thang. So it’s a ‘vanalytic’.
Sashi: Tweeterboard does not follow all Twitters. Not sure if everyone agrees with the algorithm
David Binkowski: It doesn’t count everyone’s tweets, so it would be a tool but definitely not a comprehensive one.
Interesting experiment! I have been wondering what weight Tweeterboard assigns to different actions. Way to game the ‘board!
I think Tweeterboard is a neat toy/tool for sure, but I could never think of it as wholly “accurate” as a measurement of anything. Twitter is subject to a certain degree of randomness. Exact numbers and behavior are elusive. (That may be part of what makes it so fun!)
Geoff, you are just trying to discredit Tweeterboard because I beat you in the Experiment.
Actually, I like the word “Vanalytics.” Is that new coinage? I have found very little value out of TB rather than ego-stroking and game playing like Geoff’s challenge. I actually don’t see a ton of new followers if I appear high up on the board, and to see what I am talking about you have to click through to my page anyway.
So– fun toy? Yes. More than that? Don’t think so.
But Geoff, thanks for taking the screen shot. I’m sure I can fool someone into thinking that’s cool.
Just to play devil’s advocate, would this system be more valuable if Tweeterboard was tracking all 700,000 or so Twitter users? I think they are only tracking a couple of thousand now.
Although I am suspicious of the reliability of Tweeterboard’s number crunching because of @BugMan1984’s appearance on the top (http://is.gd/Oi), I did discover another use for it yesterday.
By looking at the “Gives Love” and “Gets Love” pages of a particular user, it’s easy to discern which Twitter users make up someone’s close network. Using this method, I was able to DM a group of people to quietly promote a birthday surprise to honour a friend.
In that respect, Tweeterboard is an excellent research tool to discover who’s talking to whom the most. Conversely, when you look at your own “Love†stats, you might learn who’s been neglected in your own Twitter community and reach out.
I look at the Tweeterboard results the same way I would look at a horoscope; it is for entertainment purposes only and certainly not something to put too much stock in.
Adele McAlear
http://twitter.com/adelemcalear
Colby and Doug: No doubt, silliness at hand. Vanalytics at work!
Mack: With a significantly higher user base, and an open explanation of the algorithm, I think it would be more valuable.
This year is going to be difficult I think for guys like you and me. There is an element of understanding the way the game works combined with an element of not liking the way the game is being played. I call it the American Top 40 phase of social media http://tinyurl.com/yp3mmq . That’s a dilemma, so for now I’m just sitting back and observing.
So the TB stuff isn’t doing anything for me, what does do something for me is satisfied clients. So while some jump around and hawk their TB position, I need to make another deposit.
It was quite interesting to read about this. I posted this morning an entry about twitter at my blog. I’m still experimenting if twitter is useful for me or not.
R.
I’m a bit late to this party, but I thought I’d throw in a few comments.
You’re right, of course, that baiting people into replying to you will boost your reputation. Temporarily, anyway. It remains to be seen whether someone can do that over a sustained period of time. TB doesn’t give you a historical view of your reputation score, but if it did I think you’d see that people who had consistently high reputations would be engaged with their followers rather than just baiting them.
Part of the TB experiment (and it’s really just that–an experiment–not a product or company or whatever) is to observe how people react to this kind of measurement and ranking. So it’s been interesting to watch people focus so intently on reputation while ignoring much better conversation metrics like volume and spread. (This gets at conniereece’s comment about reciprocity.)
I agree with almost all of this (it even sounds like something I posted on my blog a few days ago):
Like many other so called rankings, it’s game-able, and subjected to the biases of the algorithm creator. Rankings are always great ways to find new Twitterers and blogs to follow, but they vary in accuracy. One key barometer to look for is multiple variables, with more variables countering individual metric weight, hopefully making for a more balanced, composite picture.
I’ve never claimed the reputation algorithm is perfect, just that it’s a better way of calculating influence than the other techniques being using (like # of followers). There’s an interesting story behind the algorithm which I’ll tell sometime in the near-ish future.
On a related note, people’s concerns about data quality are valid and I’m slowly dealing with those. But, you know, being an aggregator is hard… look at Technorati for an example of how difficult it can be to get the data side right.
About the negative box score: the box score spread shows you how many messages you’ve exchanged with a person. A negative score means you’ve sent them more than they’ve sent you. Nothing inherently bad about a negative score–it just tells you about the equity in the conversation.
I like “vanalytics” by the way. Kudos to whoever coined that. :)
- Gene
Just remember, you become what you measure. If you measure success by your ranking on Twitterboard, you will focus on @ links rather than on the conversation, creating valuable content, or giving or receiving ideas, or what ever other goal you might have.
So bizarre. Adele emailed me last night and pointed out that I’d somehow made it to #20 on the Tweeterboard. As far as I know that’s my first time there and I only added Tweeterboard MAYBE three days ago.
I think that Tweeterboard might at least appear more reliable if we understood the algorithm that was used. For me, I analyzed my “gives love” and “gets love” stats and I can with 100 percent certainty report that they are not correct. I have a handful of people I talk to ALL the time and they aren’t even on either of my lists. There’s also a significant delta between giving and receiving showing up with people I talk to, who @ me and who I @ them all the time, but it looks like they never talk to me.
I suppose I agree that Tweeterboard is fun. I wrote in my blog that it’s a tool to help finding people, but I would never add someone just because he or she is on the TB. I would click through them to their convos, see who they are having interesting convos, and more than likely add the people they are talking to before I add them.
Anyhoo… just my two cents. Nice work on the project, Geoff and Doug. Always fun whenever you can buck the system.
TweeterBoard is at least more accurate than the other Twitter LeaderBoards, Twitterholic, for example, ranks solely on “number of followers”
Full Discloser: I’m @MarkMayhew, I’m currently ranked #38 on the TweeterBoard:
http://tweeterboard.com/top-100