Tweetfind

Tweefind Applies Google Magic to Twitter Search

(Interesting article from Mashable)
Remember how Google conquered the world of search? They figured out a way to tell which web sites are more important than others, by judging how many links are pointing to them, and called it Google PageRank (it’s a bit more complex than that, but it was one of the key parts of Google’s search algorithm).

Now, Tweefind is doing something similar for Twitter. It’s a Twitter search engine which returns results based on rank, hopefully returning more relevant results and users on top.

Rank is calculated through several parameters. Creator of Tweefind, luca Filigheddu, lists them:


# followers
# following
# of tweets
# of RT he/she receives
# of replies
# of distinct users who reply
# of distinct users who retweet
# of RT he/she makes
# of links the user shares

This approach raises some interesting questions. Are Twitter users with more followers, tweets, replies or retweets more relevant in the context of real time one-to-many conversations? Is there really a “rank” on Twitter that can be calculated and be useful in real world usage? Could an approach similar to Google’s PR algorithm do for Twitter search what it did for Google?