The TweetSentiments.com API is now open to any developer interested in using Twitter for sentiment analysis. Brand monitoring is the most obvious application, but I’m sure a few of you will come up with more creative uses for the API. So far, only three calls are available. More information on how to use the API is available here.
TweetSentiments.com uses a machine learning method called support vector machines (SVM) to analyze sentiment on tweets, topics and users. It’s available as either a service or as a stand-alone application that runs behind the firewall.
If you want to see TweetSentiments.com in action, check out its updates on Twitter. The service gives a general idea of the mood of Twitter users as a whole by analyzing whether positive, negative or neutral sentiments are trending and posts regular updates.
