It’s pretty obvious that wherever you are in the world, you’re usually looking for the best bar, hotel, venue you can get for your money. And all the information is out there now, especially on live streams like Twitter. The problem is searching it and finding it. So if you could somehow match tweets to actual venues you could also use that data to rate the venue itself.
The other thing you could do would be to create trust around the actual users who submitted the information. That could form into a network of users who trusted eachother’s recommendations. There was an early implementation of this in the UK some time ago called Buzzspotr, but it never got beyond the Alpha stage and fizzled out.
Now, mobile startup Rummble is trying to crack this nut with a non-core product which just might actually super-charge their existing recommendations service.
Tremors is their new Twitter app which does the following: it attempts to match tweets to venues, based on a combination of fuzzy word matching, the general location the tweet came from and then a rough estimation of whether the Tweet was positive or negative about the venue. It’s not perfect but, of course, it will improve as more people use it. Right now it works in London, New York and Austin, Texas (the SXSW venue). These are a natural fit as they are likely to have a critical mass of Twitter users – San Francisco isn’t long now.
It’s not totally intuitive yet, and it needs more Tweets about venues – but that’s why we’re telling you about it on TechCrunch, so we can see if this thing will fly.
But already it will tell you where are the “Tweetiest” places in London. Earlier today it was Jimmy Choo’s shop on New Bond Street. Which either suggests there are some very well-heeled Twitterers out there, or that women love to tell you about what they like and don’t like, much more than men. Or have I read that wrong?
You don’t need a Rummble account to use Tremors, but if you login with your Twitter account (or you can use an existing Rummble account) Tremors will start to follow you and start to build a trust network for you, so in theory you can soon see who else on Twitter you share the same tastes and recommendations with.