We are shocked that anyone would ever use sarcasm in a review of Kim Kardashian's app. (credit: TrueRatr)
A team of students participating in Cornell University's Tech Challenge program has developed a machine learning application that attempts to break the final frontier in language processing—identifying sarcasm. This could change everything…maybe.
TrueRatr, a collaboration between Cornell Tech and Bloomberg, is intended to screen out sarcasm in product reviews. But the technology has been open sourced (and posted to GitHub) so that others can modify it to deal with other types of text-based eye-rolling.
Christopher Hong of Bloomberg acted as mentor to the interdisciplinary student team behind TrueRatr (consisting of MBA candidates, engineering, and design graduate students)—Mengjue Wang, Ming Chen, Hesed Kim, Brendan Ritter, Shreyas Kulkarni, and Karan Bir. Hong had researched sarcasm detection himself while working on his 2014 master's thesis. "Everyone uses sarcasm at some point," Hong told Ars. "Most of the time, there's some intent of harm, but sometimes it's the opposite. It’s kind of part of our nature."
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