Using Twitter Lists to Judge Influence
If you've used Twitter for awhile, you know that judging the influence of a Twitter user by their number of followers is a dicey proposition. Lots of Twitter users are obsessed with their number of followers, and work to inflate their stats in ways too numerous to mention here.
Context & Ripple Effects
This is the latest entry in a two-year argument about how to rank Twitter users. In December 2008, TechCrunch made the case that retweets, not follower counts, are what actually signal reach, and back in late 2007 ReadWriteWeb profiled Tweeterboard as an early attempt to score Twitter standing beyond raw numbers.
What changes here is that Twitter has handed users a native tool for it: Lists let respected accounts hand-pick whose updates they read, making inclusion a form of editorial endorsement. The Bivings Report argues that beats follower tallies, which users inflate freely — a point reinforced in September when Twitter's own Suggested User List drew public frustration from accounts left off it. The catch surfaced the same day via The Next Web's pickup: spammers are already working their way into Lists, so even this signal needs scrutiny. It matters because marketers were, at this point, still buying on follower totals.
First-order effects
- Marketers and PR teams vetting Twitter accounts gain a free vetting layer: placement on a trusted user's List substitutes for follower tallies that anyone can pad.
- Spammers adapt immediately — The Next Web's same-day report that junk accounts are reaching Lists means buyers cannot treat list membership as automatically clean.
Second-order effects
- Influence-measurement vendors come under pressure to fold behavioral and curatorial signals — retweets, list placements — into their rankings, since raw follower stats are demonstrably gamed.
- Twitter itself becomes an arbiter of perceived influence through its own curation, as shown by the backlash in September 2009 from users excluded from its Suggested User List.
Third-order effects
- If curated signals prove durable, influence scoring consolidates around composite measures of engagement rather than single vanity metrics — a direction Evan Williams implicitly endorsed when he described journalists as 'curators of tweets' at the Online News Association conference earlier this month.
The trend: Twitter influence measurement is migrating from raw follower counts toward curated and behavioral signals — lists, retweets, and eventually third-party scores — as each simple metric gets gamed.