TweetDeck creator Iain Dodsworth spoke with ReadWriteWeb about the future of the most popular Twitter client and the potential of mining data on tweets from InfoChimps.

Among the highlights:

Straight off the bat, an archive of tweets could form the basis of a profiler, and that’s very interesting. Sentiment analysis (which I am all over) requires that kind of base corpus.

For me, a true profiler would be akin to the holy grail. We would analyze who a person converses with, who RTs them the most, essentially all interactions. Then we would track activity metrics (how many tweets sent, replies), and then we would analyze language patterns (usage of certain words) to ascertain how they express themselves and pinpoint sentiment. Off the top of my head, this could lead to elements of intention prediction, and I’m steering TweetDeck to have this kind of very, very basic artificial intelligence at its heart.

I’m currently researching intent prediction inside high-frequency trading systems, and it’s fascinating and could directly relate to TweetDeck and social-media systems/services in general.

At its most basic, if TweetDeck could predict what the user was probably about to require next, based on current activity, then it could start to collate that data in the background—cross Twitter/Facebook/LinkedIn data, for example. I’m looking at it right now from a cross-service data gathering perspective where our servers do the gathering and hopefully get around the issues of API limits, for example.