The algorithim was tested against 66,000 reviews for books and other products listed on Amazon, where it achieved 77% precision in identifying sarky comments.

Researchers trained the algorithim to learn the sorts of words and patterns that distinguish sarcastic comments before putting it to work.

“Sarcasm recognition could contribute to the performance of review summarisations and ranking systems,” write the researchers in their paper detailing the development of Sasi, or Semi-supervised Algorithim for Sarcasm Identification.

But what of social media analysis? Mark Westaby of Spectrum Consultancy, sees little commercial potential for such an algorithim.

Sarcasm can throw up false postives when analysing online sentiment, he says, but the market is increasingly demanding more than just basic assessments of whether a comment is positive or negative. “Insight”, he says, is what brand owners and marketers want.

Whether sarcastic or not, their aim is to get to the heart of what is being expressed – to shed light on what it is exactly that people like or dislike about a product or service.

“From an academic perspective, it’s very interesting that this work is being done,” says Westaby, “but as an application in the real world, I think it has very little going for it.”