Papers with sarcasm detection research

2 papers
Reactive Supervision: A New Method for Collecting Sarcasm Data (2020.emnlp-main)

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Challenge: sarcasm detection requires large amounts of labeled data, with a high cost and noisy labels.
Approach: They propose a method that uses the dynamics of online conversations to collect sarcasm data.
Outcome: The proposed method can be adapted to other affective computing domains, opening up new research opportunities.
A Multimodal Corpus for Emotion Recognition in Sarcasm (2022.lrec-1)

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Challenge: sarcasm and emotion are often used in conversational systems to generate the right response.
Approach: They use a sarcastic expression dataset pre-annotated with 9 emotions to detect emotion . they identify and correct 343 incorrect emotion labels and label each sarkastic utterance with one of four sarcasm types.
Outcome: The proposed model outperforms state-of-the-art sarcasm detection methods by using a multimodal sarcastic detection dataset.

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