You might be had a look at my Spam Detection plugin for Elgg, here. It was during working for this, I came to know about Bayesian Filters and its usage in SPAM Detection, text classification, etc. It is one of fundamental machine learning techniques. Blah.. Blah.. You can find more details at the wikipedia - http://en.wikipedia.org/wiki/Recursive_Bayesian_estimation
Thats it with the introduction, and now I welcome you all to test drive my very first Bayesian filter implementation - Sentiment Analysis. It is every similar to the working of Semantic Extractor, except it gives only one information about the text.
Is the given text a positive feedback or negative?
It returns the final percentage of both the cases. So, just go ahead and give it a try.
Technical Specs for Nerds - The filter was trained using the test data from the dataset provided by Mark Dredze in their Multi-Domain Sentiment Dataset. I took around 25000 Amazon reviews from the dataset to train the filter, from multiple product categories.
Demo for : http://ashwanthkumar.in/labs/sentiment/sentiment.php - It uses the content from Mashable for Samsung Galaxy S Android Smart phone (Link: http://mashable.com/2010/07/26/galaxy-s-review/)
Any feedback is highly appreciated.