A new algorithm that can recognize sarcasm may help improve the subtler aspects of human-computer interactions. An Israli research team built the algorithm by scanning 66,000 Amazon reviews and manually tagging sentences which contained instances of sarcasm. After identifying patterns, and classifying them into different sarcastic classes, the group set out to train the computer
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The algorithms were then trained on that seed set of 80 sentences from the collection of reviews. These annotated sentences helped the algorithm learn what sorts of words and patterns distinguish sarcastic remarks – those that mean the opposite of what they literally convey, or that convey a sentiment inconsistent with the literal reading.
They then turned the algorithm loose on an evaluation set. Pattern evaluation efficiency scored accurately 81 percent of the time, while the overall precision of the pattern recognition/sarcasm categorizing algorithm was accurate in 77 percent of instances. Not bad for a computer’s first shot at interpreting the human sense of humor.