Abstract
The University of Central Florida invention is an interpretable deep learning model to detect sarcasm within social media text. Since social media enables businesses to advertise their products, build brand value, and reach out to their customers, businesses need to process customer feedback in posts and tweets. Sentiment analysis identifies the emotion, either positive, negative, or neutral, associated with these social media texts. The presence of sarcasm in texts is the main hindrance to the performance of sentiment analysis. This invention assists with the identification of sarcastic cues to train text classification systems.
Benefit
Provides the complexity needed to decode sarcasm in textEnables the interpretability of what the model learned to perform its taskMarket Application
Customer serviceMarketing research, opinion mining, information classification
Brochure
