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.
Published 7 May 2021
Sentiment analysis – the process of identifying positive, negative, or neutral emotion – across online communications has become a growing focus for both commercial and defense communities. Sentiment can be an important signal for online information operations to identify topics of concern or the possible actions of bad actors. The presence of sarcasm – a linguistic expression often used to communicate the opposite of what is said with an intention to insult or ridicule – in online text is a significant hindrance to the performance of sentiment analysis.
Sentiment analysis – the process of identifying positive, negative, or neutral emotion – across online communications has become a growing focus for both commercial and defense communities. Understanding the sentiment of online conversations can help businesses process customer feedback and gather insights to improve their marketing efforts. From a defense perspective, sentiment can be an important
E-Mail
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
New AI detects sarcasm in social media
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 developed a technique that accurately detects sarcasm in social media text.