Figurative language (such as metaphors or sarcasm) has proven to be challenging for natural language processing tasks such as sentiment analysis. Therefore, approaches that understand (detect/interpret) figurative language have been reported in the past. In the context of public health monitoring, figurative language detection and interpretation assumes importance because figurative language may reflect emotional states arising due to a health condition. The project aims to apply advances in machine learning to improve figurative language processing and public health monitoring using textual datasets.





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