The character Liz Lemon, played by Tina Fey, in the TV show “30 Rock,” demonstrates her masterpiece eye roll reserved for sarcastic responses. (Source:

Researchers Close in on Teaching Algorithms How to Perceive Sarcasm, OK?

It may have taken Sheldon Cooper on The Big Bang Theory years to master the recognition of sarcasm from one of his friends, and even at that, I’m not sure he ever really did. And it is generally thought that sarcasm doesn’t translate well into digital communications. Oh, but it does. (Eye roll.)

Researchers in China say they’ve created sarcasm detection AI that achieved state-of-the-art performance on a dataset drawn from Twitter. The AI uses multimodal learning that combines text and imagery since both are often needed to understand whether a person is being sarcastic.

The researchers argue that sarcasm detection can assist with sentiment analysis and crowdsourced understanding of public attitudes about a particular subject. In a challenge initiated earlier this year, Facebook is using multimodal AI to recognize whether memes violate its terms of service. Khari Johnson on has written a story that says digital sarcasm can be perceived by algorithms.

The researchers’ AI focuses on differences between text and imagery and then combines those results to make predictions. It also compares hashtags to tweet text to help assess the sentiment a user is trying to convey.

“Particularly, the input tokens will give high attention values to the image regions contradicting them, as incongruity is a key character of sarcasm,” the paper reads. “As the incongruity might only appear within the text (e.g., a sarcastic text associated with an unrelated image), it is necessary to consider the intra modality incongruity.”

On a dataset drawn from Twitter, the model achieved a 2.74% improvement on a sarcasm detection F1 score compared to HFM, a multimodal detection model introduced last year. The new model also achieved an 86% accuracy rate, compared to 83% for HFM.

The paper was published jointly by the Chinese Academy of Sciences and the Institute of Information Engineering, both in Beijing. The paper was presented this week at the virtual Empirical Methods in Natural Language Processing (EMNLP) conference.

The AI is the latest example of multimodal sarcasm detection to emerge since AI researchers began studying sarcasm in multimodal content on Instagram, Tumblr and Twitter in 2016.

For those rolling your eyes about digital sarcasm, there is more to learn at the link below.