Sarcasm Detection Using Deep Learning With Contextual Features

Our work focuses on detecting sarcasm in tweets using deep learning extracted features combined with contextual handcrafted features. A feature set is from a Convolutional Neural Network (CNN) architecture before it carefully sets. These sets are created based their respective explanations. Each specifically designed for the sole task of detection. The objective to find most optimal Some good go even when used independence. Other not really significant without any combination. results experiments positive terms Accuracy, Precision, Recall and F1-measure. combination classified few machine techniques comparison purposes. Logistic Regression found be best classification algorithm this task. Furthermore, result recent works performance each also shown as additional information.