(notes on behavioral categorization of Twitter accounts)
I don’t follow a lot of people on Twitter, but I still sometimes have trouble deciding whether the accounts I’m following are worth it. Folks with much longer follow lists presumably have even harder going.
Enter The Twit Cleaner, a (sadly, as of late 2013, defunct) service that scans your follow list and automatically categorizes the behavior of everyone on it. They have some straightforward heuristics for deciding whether someone is worth following, mostly documented in their FAQ:
Q. How are the (potential) bad guys broken down?
A. The possible categories are:
Dodgy - spam phrases, @ spamming, duplicate links etc
Absent - No updates in a month, or fewer than 10 tweets.
Repetitive - High numbers of duplicate tweets or links
Flooding - So high volume you can’t see anyone else
Non-Responsive - No interaction & those that follow back < 10%
Little New Content - Retweeting lots or just posting quotes
This is generally a good scheme, but its focus on conversational use of Twitter means that it misidentifies a few types of legitimate account as unsavory. I think a few special case categories would go a long way to making the service’s advice more useful.
These are the Twitter equivalent of a news ticker—they broadcast announcements related to something, but they don’t converse with people (as a general rule). The Cleaner dings them as
dodgy behavior: tweeting the same links all the time and/or
not interactional: hardly follow anyone. Examples include @NBCOlympics, @CDCemergency, @asym, @Astro_Soichi, and (ironically) @TwitCleaner itself (the problem here appears to be public
@somebody, your report is ready at directed tweets when direct messages fail).
These can probably be machine-identified as extreme outliers in follower-to-followed ratio. @asym and @Astro_Soichi don’t follow anyone; @NBCOlympics and @CDCemergency follow less than 0.1% of their follower numbers. @TwitCleaner likes to follow users of the service, though; maybe they should just whitelist themselves? Also, if Twitter-verified users are not already whitelisted (I wasn’t able to tell from my own report), perhaps they should be.
Lurkers are the opposite of announcement channels: they just read Twitter, they never post anything. Lurking is a time-honored tradition on the Internet and people shouldn’t be penalized for it. I have several lurkers on my follow list just on the off chance that they might start posting in the future.
Accounts that have never posted at all should be distinguished from accounts that post rarely. (The latter are often spammers. Lately Twitter itself has gotten a lot better about finding and banning spammers, but they still turn up now and then.)
Fictional character accounts
There are any number of fictional characters who regularly use Twitter—that is, their authors write and post tweets under their names, usually to provide a bonus story line, or to implement the fourth wall mail slot. Examples include @Othar of Girl Genius and the entire cast (caution: mildly NSFW; @pintsize0101 consistently links to egregiously NSFW images of the
where’s my brain bleach variety) of Questionable Content. Fictional characters may absent themselves for long periods because the bonus story line is on hold (Othar recently didn’t post anything for four months but is now back) and might not follow anyone but other characters from the same fictional world (the QC cast does this); both things get them unfairly dinged by the Cleaner.
It probably isn’t possible to identify fictional accounts in a mechanical way. However, you could pick out cliques in the follow graph, sets of accounts that are followed by many but that follow no one but each other, as deserving human attention. If Twitter implemented some sort of account-labeling scheme that would let the people behind the curtain mark accounts as fictional characters, that would be awesome.