Computer researchers have developed Artificial Intelligence, that can detect Sarcasm in Social Media.
Individuals use Social Media for personal and official communication. Products and Services are being sold by different companies through Social Media. It has become the most important mode of communication.
Sentiment Analysis refers to an automated process of identifying the emotions associated with a text. It can be positive, negative or neutral in nature. Sentiment Analysis is used for correctly identifying emotional communication and providing proper customer feedback and support by social media platforms.
Computer Science Researchers at the University of Central Florida have developed a Sarcasm Detector, a technique to accurately detect sarcasm in social media text.
“The presence of sarcasm in text is the main hindrance in the performance of sentiment analysis,” says Assistant Professor of Engineering Ivan Garibay ’00MS ’04PhD. “Sarcasm isn’t 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 better classify the input text.”
Source of information: TexhXplore – article published on 7th May 2021.
Read the full article here
