Dataset Analysis and Augmentation for Emoji-Sensitive Irony Detection
empirical methods in natural language processing(2019)
Abstract
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.
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Key words
augmentation,emoji-sensitive
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