Luca Filigheddu is a smart guy who’s been playing with Twitter a lot recently. Check out his post on link conversion rates, for example. He’s using the tr.im tracking tool to track conversion rates on his posts, and experimenting with how to goose those rates with multiple tweets.
Recently Luca announced TweeFind, a rank based search engine for Tweets. Rather than simply search chronologically for twitter messages, Luca is ranking those messages using an algorithm that takes into account the number of followers that the user has – something like the Google PageRank algorithm.
Novel? Yes. Will it produce the relevant results that he seeks? Time will tell. It’s hard to know today whether the volume of tweets and the primitive search tools that exist have created a large enough user problem to warrant this kind of solution.
But kudos to Luca for building TweeFind and putting it out there for users to try.