Computer science researchers at the University of Central Florida have developed an artificial intelligence-based sarcasm detector for posts on social media platforms.
Sarcasm isn't always easy to identify in conversation, and is also challenging for a computer program. CFU associate professor Ivan Garibay and doctoral student Ramya Akula describe their work in "Interpretable Multi-Head Self-Attention Architecture for Sarcasm Detection in Social Media," published in the journal Entropy.
"In face-to-face conversation, sarcasm can be identified effortlessly using facial expressions, gestures, and tone of the speaker," Akula says. None of these cues are readily available in textual communication.
The team taught the computer model to find patterns that often indicate sarcasm and combined that with teaching the program to correctly pick out cue words in sequences that were more likely to indicate sarcasm.
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