Representing Social Media Users for Sarcasm Detection

@inproceedings{Kolchinski2018RepresentingSM,
  title={Representing Social Media Users for Sarcasm Detection},
  author={Y. Alex Kolchinski and Christopher Potts},
  booktitle={EMNLP},
  year={2018}
}
We explore two methods for representing authors in the context of textual sarcasm detection: a Bayesian approach that directly represents authors' propensities to be sarcastic, and a dense embedding approach that can learn interactions between the author and the text. Using the SARC dataset of Reddit comments, we show that augmenting a bidirectional RNN with these representations improves performance; the Bayesian approach suffices in homogeneous contexts, whereas the added power of the dense… CONTINUE READING
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CASCADE: Contextual Sarcasm Detection in Online Discussion Forums

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