Neural Network Approach for Irony Detection from Arabic Text on Social Media

Irony plays an important part in human social interaction which is used to emphasize occurrences that deviate from the expected. Humans manipulate each other in a very negative way by writing the opposite of what they mean. However, irony detection is a complex task even for humans. In this research, we study the problem of irony detection as a classification problem and utilized the dataset offered by the IDAT workshop. We also propose a classification system for detecting irony in the Arabic tweets using neural networks.