Orange vs NLTK for Content Classification in Python
I don't know Orange, but +1 for NLTK:
I've successively used the classification tools in NLTK to classify text and related meta data. Bayesian is the default but there are other alternatives such as Maximum Entropy. Also being a toolkit, you can customize as you see fit - eg. creating your own features (which is what I did for the meta data).
NLTK also has a couple of good books - one of which is available under Creative Commons (as well as O'Reilly).
We need a content classification module. Bayesian classifier seems to be what I am looking for. Should we go for Orange or NLTK ?