Looking for Sarcasm

Have been looking at the general problem of how to detect demographic and personality indicators via twitter streams.  Here is an example described of detecting sarcasm . 

" ... Researchers at the University of Lisbon have developed a machine-learning system that can identify sarcasm on Twitter by examining a user's past tweets. The system uses the past tweets to develop a picture of a person that is detailed enough to guess when they are being sarcastic. The researchers say the system predicts sarcasm with an accuracy of 87 percent, which is slightly better than other existing methods. However, by learning to detect sarcasm without human input, the system should be easy to use. In addition, the new approach should work for any language and any online platform where posting history is available. "The key innovation is realizing you can build a model of the user merely based on what they have said in the past," says University of Lisbon researcher Silvio Amir. Monash University researcher Mark Carmen notes it should be straightforward to integrate the new approach with other types of social media analysis, such as tracking users' emotions or stock market trends. Analyzing sarcasm also could be a great help to marketers and customer service teams, as well as virtual assistants such as Apple's Siri. ...  "

See previous coverage of sarcasm below.