Computer Science researchers from the University of Central Florida (UCF) have developed a tool that can detect sarcasm in any text. It was developed after a long period of research and mainly targets social media platforms. The main aim of the tool is to accurately understand and respond to customer feedback on social media. It is expected that the sarcasm detector will prove to be fruitful for social media content creators.
Sarcasm Detector: A new tool developed by Researchers of UCF
The team at the UCF made new algorithms to detect patterns that often show sarcasm by precisely picking out cue words in sequences that were more prone to indicate sarcasm. They performed this function by feeding the algorithms with large data sets and then verifying their accuracy.
The Assistant Professor of engineering at UCF, Ivan Garibay said,
The presence of sarcasm in the text is the main hindrance in the performance of sentiment analysis. Sarcasm is not always easy to identify in conversation, so you can imagine it’s pretty challenging for a computer program to do it and do it well. We developed an interpretable deep learning model using multi-head self-attention and gated recurrent units. The multi-head self-attention module aids in identifying crucial sarcastic cue-words from the input, and the recurrent units learn long-range dependencies between these cue-words to classify the input text better.
The sarcasm detector will assist in developing a better understanding of customer feedback on social media platforms. Customer feedback is pivotal for any brands’ success, but it is very labor-intensive. However, the efforts of computer science researchers at the University of Central Florida must be lauded who have developed a sarcasm detector to help the content creators.