I am working on a group project for my capstone course and we have been tasked with creating a sentiment analysis tool with Python business logic and (L/W)AMP everything else.
We have good feedback for every part of our project plan except for feature extraction. One of our advisors insists that we should have ~15 different kinds of features.
Currently we only use unigrams and are having a hard time finding others that are practical to implement with our small set of data (~50 items) and within our time limit (~2 weeks to fully implement).
What are feature extraction techniques that are useful for sentiment analysis and work on smaller datasets? They should be able to be implemented quickly or already exist in a Python library.