sentiment analysis nltk python I'd like to perform sentiment analysis on stock comment using scikit and nltk. I already have about 100 comments on different stocks like "this stock will rock" which I marked as positive (1) or "this is doomed stock" which I marked as negative(0). So I'd like to train classifier which can tell whether new comments I add are negative or positive. So my question is how to perform it. I've already searched the Net but all I found was movie review sentiment analysis which is quite remote from the topic.
What you're doing right now is a traditional classification using supervised learning. This is a great method for predicting outcomes, but I suspect there are much better ways to complete this sentiment analysis project you're working on.

Without knowing what the goal of your analysis is, I would suggest you look at the NLTK package. A lot of work has been done to idenify how positive or negative a collection of words is, and you could piggyback on the work of some really smart people. 

If you're having trouble starting, you can look at NLTK's how-to tutorial, some Kaggle kernels, or find some articles online.

Good luck!