A UCF team developed a technique that accurately detects sarcasm in a social media text.
Recognizing sarcasm in textual online communication is no easy task as none of these cues is readily available.
Washington: Properly understanding and responding to customer feedback on social media platforms is crucial for brands, and it may have just gotten a little easier thanks to new research by computer science researchers at the University of Central Florida who have developed a sarcasm detector.
Social media has become a dominant form of communication for individuals, and for companies looking to market and sell their products and services.
Researchers develop artificial intelligence that can detect sarcasm in social media ANI | Updated: May 11, 2021 23:08 IST
Washington [US], May 11 (ANI): Properly understanding and responding to customer feedback on social media platforms is crucial for brands, and it may have just gotten a little easier thanks to new research by computer science researchers at the University of Central Florida who have developed a sarcasm detector.
Social media has become a dominant form of communication for individuals, and for companies looking to market and sell their products and services. Properly understanding and responding to customer feedback on Twitter, Facebook and other social media platforms are critical for success, but it is incredibly labour-intensive.
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IMAGE: Dr. Garibay is investigating ways to make artificial intelligence smarter when it comes to detecting and appropriately responding to human emotions. view more
Credit: University of Central Florida
Computer science researchers at the University of Central Florida have developed a sarcasm detector.
Social media has become a dominant form of communication for individuals, and for companies looking to market and sell their products and services. Properly understanding and responding to customer feedback on Twitter, Facebook and other social media platforms is critical for success, but it is incredibly labor intensive.
That s where sentiment analysis comes in. The term refers to the automated process of identifying the emotion either positive, negative or neutral associated with text. While artificial intelligence refers to logical data analysis and response, sentiment analysis is akin to correctly identifying emotional communication. A UCF team develo
One of the greatest strengths of artificial intelligence (AI) – its ability to learn and adapt over time – could also be its Achilles’ heel.
When a product or service can learn and evolve through experience and interactions with human beings, it can be hard to pinpoint who is responsible when something goes wrong. How to allow for this dynamism and, at the same time, build trust in artificial intelligence was one of the key topics of debate in a Science|Business webinar entitled:
AI: Who is Liable? - the latest in a series produced by Science|Business Data Rules group.
“You see association effects where man and machine work together in a specific context, but it is unclear what the machine has learned from man, and what man has learned from the machine,’ noted Evert Stamhuis, senior fellow at the Jean Monnet Centre of Excellence Digital Governance, Erasmus University Rotterdam.