A Large Self-Annotated Corpus for Sarcasm

We introduce the Self-Annotated Reddit Corpus (SARC), a large corpus for sarcasm research and for training and evaluating systems for sarcasm detection. The corpus has 1.3 million sarcastic statements -- 10 times more than any previous dataset -- and many times more instances of non-sarcastic statements, allowing for learning in both balanced and unbalanced label regimes. Each statement is furthermore self-annotated -- sarcasm is labeled by the author, not an independent annotator -- and provided with user, topic, and conversation context. We evaluate the corpus for accuracy, construct benchmarks for sarcasm detection, and evaluate baseline methods.

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Datasets


Introduced in the Paper:

SARC

Results from the Paper


Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Sarcasm Detection SARC (all-bal) Bag-of-Bigrams Accuracy 75.8 # 2
Sarcasm Detection SARC (pol-bal) Bag-of-Bigrams Accuracy 76.5 # 1
Sarcasm Detection SARC (pol-unbal) Bag-of-Words Avg F1 27.0 # 1

Methods


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