Another Way to Classify Twitter Users
April 28th, 2008 | Published in Twitter, social media | 1 Comment
Recently, blogger Michael Klier came introduced a Greasemonkey script for identifying Twitter spammers based on the recommendations of a site called "The Twitter Blacklist." The site, which determines who is a Twitter spammer based on a "follow factor" ratio, has blocked 164 spammers to date. Michael’s script looks up the username of the visited Twitter profile, and, if the user is identified as a spammer, displays a hard to miss warning message at the topic of the screen:
(image via CH!MER!C.de)
Inspired by this script, blogger Andreas Gohr decided to create a script of his own using Evan Prodromou’s new scale for deciding who to follow.
The scale Evan proposed is as follows:
- 1:5 = twittercaster
- 1:2 = notable
- 1:1 = socially healthy
- 2:1 = newbie or social climber
- 5:1 = twitter spammer
This new script not only identifies Twitter spammers, but also classifies all Twitterers into categories based on their following to follower ratio, and displays their category in a colored bar at the top of the screen:
(image via splitbrain)
Considering Louis Gray’s recent classification brouhaha which categorized people as listeners, middle ground, conversationalists, or megaphones, it’s interesting to compare his findings with the classifications made by the script.
Below are Louis’s findings updated to include the new classification level as determined by this greasemonkey script:
Twitter’s Listeners (Ratio of Updates to Followers of Less than 1)
@om
Noise Ratio: 0.06 / twittercaster
@erickschonfeld
Noise Ratio: 0.08 / notable
@nbradbury
Noise Ratio: 0.08 / twittercaster
@techcrunch
Noise Ratio: 0.11 / twittercaster
@jasoncalacanis
Noise Ratio: 0.18 / newbie or social climber
@gaberivera
Noise Ratio: 0.23 / notable
@ev
Noise Ratio: 0.25 / twittercaster
@louisgray
Noise Ratio: 0.49 / socially healthy
@scobleizer
Noise Ratio: 0.50 / socially healthy
@dannysullivan
Noise Ratio: 0.79 / twittercaster
@gapingvoid
Noise Ratio: 0.90 / twittercaster
Twitter’s Middle Ground (Ratio of Updates to Followers of 1 to 2.0)
@jowyang
Noise Ratio: 1.03 / socially healthy
@tamar
Noise Ratio: 1.14 / notable
@loiclemeur
Noise Ratio: 1.16 / socially healthy
@adamostrow
Noise Ratio: 1.19 / socially healthy
@iankennedy
Noise Ratio: 1.20 / notable
@mashable
Noise Ratio: 1.28 / twittercaster
@susanmernit
Noise Ratio: 1.31 / newbie or social climber
@nicolesimon
Noise Ratio: 1.52 / socially healthy
@elliottng
Noise Ratio: 1.59 / socially healthy
@tonyhung
Noise Ratio: 1.67 / socially healthy
@calebelston
Noise Ratio: 1.72 / newbie or social climber
@shelisrael
Noise Ratio: 1.81 / notable
@ebrage
Noise Ratio: 1.98 / socially healthy
Twitter’s Conversationalists (Ratio of Updates to Followers of 2.0 to 5.0)
@centernetworks
Noise Ratio: 2.02 / notable
@markevans
Noise Ratio: 2.15 / notable
@sarahintampa (me!)
Noise Ratio: 2.22 / socially healthy
@marshallk
Noise Ratio: 2.26 / socially healthy
@mariosundar
Noise Ratio: 2.26 / notable
@charlieanzman
Noise Ratio: 2.29 / newbie or social climber
@chrisbrogan
Noise Ratio: 2.45 / socially healthy
@mathewi
Noise Ratio: 2.50 / notable
@mukund
Noise Ratio: 2.77 / newbie or social climber
@rizzn
Noise Ratio: 2.99 / notable
@parislemon
Noise Ratio: 3.07 / socially healthy
@nickhalstead
Noise Ratio: 3.35 / notable
@duncanriley
Noise Ratio: 3.43 / notable
@jeffisageek
Noise Ratio: 3.67 / socially healthy
@krynsky
Noise Ratio: 4.36 / notable
@pkedrosky
Noise Ratio: 4.68 / twittercaster
@fredericl
Noise Ratio: 4.95 / socially healthy
Twitter’s Megaphones (Ratio of Updates to Followers of more than 5.0)
@stevenhodson
Noise Ratio: 5.12 / socially healthy
@stephtara
Noise Ratio: 6.42 / notable
@bgolub
Noise Ratio: 6.79 / newbie or social climber
@idonotes
Noise Ratio: 7.91 / notable
@solacetech
Noise Ratio: 8.50 / newbie or social climber
@fourlittlebees
Noise Ratio: 9.06 / socially healthy
@corvida
Noise Ratio: 9.75 / notable
What Does It Mean?
As you can tell, this represents a completely different way to categorize users - some of our megaphones become healthy and some of our listeners become twittercasters. But is this way any more helpful or accurate?
And then there is Dave Winer, who has his own method to determine who’s responsible for "Twitter spewage." But who is right?
I personally am using an auto-follow/auto-welcome script, something I turned on after Marshall posted the RWW team’s Twitter usernames in a recent post since I wanted to add the readers that were following me. That makes me socially healthy according to this script, but to be honest, if left to my own devices, I probably wouldn’t have added everyone that had added me…at least not right away. Scoble, too, had auto-followed people for quite some time, until he maxed out at 20,000. But here he sits at "socially healthy." I don’t know about you, but I wouldn’t call Scoble’s user of Twitter socially healthy!
What do you think?
(P.S. Thanks to Corvida for discovering this script!)
- Corvida,
- Ontario Emperor,
- Evan Prodromou,
- Charlie Anzman,
- Anthony Farrior
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I'm not a fan of the ratio approach... if you can't tell from my comment on the blog. ;)
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Ooh.. Matt's comment is longer than the post. Matt, you need to blog.
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Wow LG...
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I WISH I was a newbie! :)
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Louis: I'm not sure if that's a reprimand... If I broke some unspoken rule by leaving a long blog comment then I guess (with tongue in cheek) I apologize. Not because I'm sorry for my opinion but because I want it to be known that I meant no offense by sharing it with Sarah. I feel like I can't win for losing these days; You know what I'm saying?
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Perhaps all blog comments should be done in Haiku form. :)
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Ontario: lol. great idea, but I think Louis and MG might feel a little stepped on if we all started busting out the haiku everywhere.... http://www.techaiku.com/ (which just so happens to be great stuff, subscribe to that... it's not updated ultra often, but it's classic! Quality over quantity.)
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