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Deep and dense sarcasm detection, Pelser et al., 2019

Paper, Tags: #nlp, #sarcasm-detection

In this paper we propose a deep 56 layer network implemented with dense connectivity to model the isolated utterance and extract richer features therein.

Low-level features are shown to be used during the formation of the final feature maps.

Our results demonstrate that whilst context is often needed to classify sarcasm; there is additional local information present that previous approaches have not taken advantage of