If you have some resources (media channels, blogs, etc) about the domain you want to explore, you can create your own corpus.
I do this in python:
- using Beautiful Soup http://www.crummy.com/software/BeautifulSoup/ for parsing the content that I want to classify.
- separate those sentences meaning positive/negative opinions about companies.
- Use NLTK to process this sentences, tokenize words, POS tagging, etc.
- Use NLTK PMI to calculate bigrams or trigrams mos frequent in only one class
Creating corpus is a hard work of pre-processing, checking, tagging, etc, but has the benefits of preparing a model for a specific domain many times increasing the accuracy. If you can get already prepared corpus, just go ahead with the sentiment analysis ;)
