Researchers at the University of Turin and Yahoo! have developed software that can identify the expression of sarcasm on social media and the Web.
Turin professor Rossano Schifanella says the project began with a crowdsourcing program asking people from several English-speaking countries to tag social media posts as sardonic or not. They first evaluated text-only statements, then statements with images. In most cases, the presence of a visual image helped identify a sarcastic message, while linguistic cues that expressed sarcasm to the participants included wordplay as well as punctuation.
The next step was to write an algorithm that mathematically represented the knowledge gained from the crowdsourcing program. Schifanella says this enabled a machine to tap that baseline data to examine new posts and decide whether they were sarcastic. The computer picked up on the sarcasm 80 percent to 89 percent of the time, and the results sometimes varied according to the platform and the type of features used to detect the sarcasm.
Grammarly research director Joel Tetreault, formerly with Yahoo!, says advances in computer-processing power and large social networks have facilitated this type of neural network-based machine learning. Other researchers say this research constitutes a key step toward computerized natural-language comprehension.
From Scientific American
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