‘Sentiment mining’ – i.e. trying to gauge the Public’s attitude towards an institution, product, firm (etc. etc.) though automatic analysis of Social Media posts (etc. etc.) is now considered an essential tool for market researchers and ‘reputation managers’.
But there are problems. One of which is sarcasm. Given its prevalence, serious errors can be introduced in a Sentiment Mining Picture if it’s not reliably detected.
Work on Automatic Sarcasm Detection began in the mid 2000s – see, for example, Joseph Tepperman, David Traum, and Shrikanth S. Narayanan. “Yeah right”: Sarcasm recognition for spoken dialogue systems. In Proceedings of InterSpeech, pp. 1838–1841, Pittsburgh, PA, sep 2006.
Since then, work on refining Automatic Sarcasm Detection Algorithms has flourished. Here is a list of but-a-few of the many hundreds of scholarly works which address the issue (in no particular order).
Note: One of the simplest methods, pointed out in An Approach to Detect Sarcasm in Tweets (amongst other papers above) is to look for posts or Tweets (etc. etc.) which use the hashtag #Sarcasm.
Research research by Martin Gardiner