Sarcasm Detection News Today : Breaking News, Live Updates & Top Stories | Vimarsana

This paper presents a deep learning-based framework to detect sarcasm in relation to time. Deep N-gram features generated using the FastText algorithm, combined with temporal handcrafted temporal features are used to train several machine learning classifiers. Experimental results show that Logistic Regression performs the best among all the classifiers. The introduction of the handcrafted temporal features has also whosn to improve overall detection performance when compared to existing works in the field.

Abstract Our work focuses on detecting sarcasm in tweets using deep learning extracted features combined with contextual handcrafted features. A feature set is extracted from a Convolutional Neural Network (CNN) architecture before it is combined with carefully handcrafted feature sets. These handcrafted feature sets are created based on their respective contextual explanations. Each feature sets are specifically designed for the sole task of sarcasm detection. The objective is to find the most optimal features. Some sets are good to go even when it is used in independence. Other sets are not...