Hoping to get back to this very soon after the last year off. It’s a long story, and I’ll be posting about it soon.
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The one thing that twitterers fear is a fatal influx of spammers as the popularity of the service grows. Right now it’s a fairly clean service, and the ability to easily block users makes it a challenge for spammers to get a foothold. This doesn’t mean that some are not trying. So to address this a new website has popped up, the Twitter Black List. The service uses a formula that calculates the follow/follower ratio for a user and grades them as:
1:5 = twittercaster, 1:2 = notable, 1:1 socially healthy, 2:1 newbie or social climber, 5:1 twitter spammer.
Another tool, Twitter Twerp Scan uses similar logic to scan your followers and make suggestions on who to block.
Unfortunately going by this ratio alone you are going to catch a lot of legit users. Lets not forget Scobleizers’ advice that it’s not who follows you, it’s who you follow. Heck, going by this criteria I’m amost a spammer. The problem with the Blacklist is that it seems to lable people as “… known spammers and other morons on Twitter…” without any reguard to the content they post. Sure, some of the posts are mundane, but I would not lable someone like flyaxe as a spammer. The guy follows several thousand people sure, but a spammer? I have a hard time with the concept that a person should get the ban hammer just because they follow a lot of people. This is how some people choose to use twitter, it doesn’t harm the people they follow, and if they are not spamming you, who cares? If we are going to scrutinize based on a follow/follower ratio, wouldn’t it make more sense to go the other way and take a harder look at people who are followed by way more people than they follow?
While I agree that a blacklist of twitter-spammers is a good thing, probably approaching necessary, some logic other than just an arbitrary ratio of followers needs to be used to determine who is a spammer and who is just trying to get the most out of twitter. A more indepth analysis of tweets is needed, and without some other info (such as Blocked stats for users) it probably can’t be automated. The only tell-tale way to tag a spammer would be to look at links in tweets, but how to do you sort out the spammers from the Scobleizers or mashables?
I’m playing with some themes (may just end up paying someone for one). Until then, the themes may change. Just looking for something easy on the eyes until the final theme is done.
