If you're new to NLP, I recommend getting a book like Natural Language
Processing with Python, using the Python Twitter API, and writing a Bayesian
spam classifier. If you're less new, I've been working in sentiment
classification for a while now and it's a lot of fun. Also things like
Hello folks. I'm Jen. Just moved to SF from Scotland where I ran a data
intelligence startup which dug into Twitter sentiment analysis (see
festbuzz.com for an example).
I'm consulting, writing, speaking and doing a day job at a Silicon Valley
tech co. for now, but I have a list as long as my arm
... but the response comes back in
one second (or just really really fast).
Any help appreciated...
Brian Roy
justSignal
--
Jennie Lees
Founder, Affect Labs
jen...@affectlabs.com
http://twitter.com/jennielees
TweetDeck (http://www.tweetdeck.com) is the obvious answer, you can group
your contacts into different panels and thus not have the noisy drown out
the intelligent.
Pretty sure other clients do it too, to different extents - a bit of
googling and trying them out won't hurt if TD's not to your
On Sun, Jul 19, 2009 at 12:02 AM, M. Edward (Ed) Borasky
zzn...@gmail.comwrote:
Man, it is so good to hear this from someone who's actually done it!
The other point, though, is that the real thing, even traffic /
social network analysis, is compute-resource intensive and requires a
kind of
other tweets up/down manually'
thing; it's such a jump to get that level of user interaction frequently
enough to be meaningful.
-J
--
Jennie Lees
Founder, Affect Labs
jen...@affectlabs.com
http://twitter.com/jennielees
