What A Sunny Day ☂️: Toward Emoji-Sensitive Irony Detection

Shirley Anugrah Hayati, Aditi Chaudhary, Naoki Otani, Alan W Black
Carnegie Mellon University


Irony detection is an important task with applications in identification of online abuse and harassment. With the ubiquitous use of non-verbal cues such as emojis in social media, in this work we aim to study the role of these structures in irony detection. Since the existing irony detection datasets have <10% ironic tweets with emoji, classifiers trained on them are insensitive to emojis. We propose an automated pipeline for creating a more balanced dataset.