Some will surely wonder if the point of such research goes beyond devising software that can make the C++ set crack up at hackathons. Thankfully, it does. The goal of computational humor, and of computational linguistics as a whole, is to design machines akin to the shipboard computer on “Star Trek” — ones that can answer open-ended questions and carry on casual conversations with human beings, even William Shatner.
To get around that cognitive complexity, computational humor researchers have by and large taken a more concrete approach: focusing on simple linguistic relationships, like double meanings, rather than on trying to model the high-level mental mechanics that underlie humor.
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As it turns out, this is one of the most challenging tasks in computer science. Like much of language, humor is loaded with abstraction and ambiguity. To understand it, computers need to contend with linguistic sleights like irony, sarcasm, metaphor, idiom and allegory — things that don’t readily translate into ones and zeros.