To Help People with Autism, Researchers Develop System to detect Sarcasm on Social Media

Based on machine translation, the new system, called Sarcasm SIGN (sarcasm Sentimental Interpretation GeNerator), turns sarcastic sentences into honest (non-sarcastic) ones

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Researchers Develop System to detect Sarcasm on Social Media. Pixabay
  • In order to teach the system to produce accurate interpretations, the researchers compiled a database of 3,000 sarcastic tweets
  • Based on machine translation, the new system, called Sarcasm SIGN (sarcasm Sentimental Interpretation GeNerator)
  • The system was examined by a number of (human) judges, who gave its interpretations high scores of fluency and adequacy

New York, June 24, 2017: To help people with autism, who often have difficulty interpreting sarcasm, irony and humour, researchers have developed a system for interpreting sarcastic statements posted on social media.

“There are a lot of systems designed to identify sarcasm, but this is the first that is able to interpret sarcasm in written text,” said Lotam Peled from Technion — Israel Institute of Technology.

“We hope in the future, it will help people with autism and Asperger’s,” Peled, who developed that system under the guidance of Assistant Professor Roi Reichart, added.

Based on machine translation, the new system, called Sarcasm SIGN (sarcasm Sentimental Interpretation GeNerator), turns sarcastic sentences into honest (non-sarcastic) ones.

It will, for example, turn a sarcastic sentence such as, “The new ‘Fast and Furious’ movie is awesome. #sarcasm” into the honest sentence, “The new Fast and Furious movie is terrible.”

Despite the vast development in this field, and the successes of sentiment analysis applications on “social media intelligence,” existing applications do not know how to interpret sarcasm, where the writer writes the opposite of what he/she actually means.

In order to teach the system to produce accurate interpretations, the researchers compiled a database of 3,000 sarcastic tweets that were tagged with #sarcasm, where each tweet was interpreted into a non-sarcastic expression by five human experts.

In addition, the system was trained to identify words with strong sarcastic sentiments and to replace them with strong words that reveal the true meaning of the text.

The system was examined by a number of (human) judges, who gave its interpretations high scores of fluency and adequacy, agreeing that in most cases it produced a semantically and linguistically correct sentence, the American Technion Society (ATS) which provides critical support to the Technion – Israel Institute of Technology, said in a statement. (IANS)