Papers › A Large Self-Annotated Corpus for Sarcasm
A Large Self-Annotated Corpus for Sarcasm
Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli
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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c3ddefbcc6adaf75 · report
Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Sarcasm Detection | SARC (all-bal) | Bag-of-Bigrams | Accuracy | 75.8 | #2 of 2 | Archive leaderboard | report |
| Sarcasm Detection | SARC (pol-bal) | Bag-of-Bigrams | Accuracy | 76.5 | #1 of 2 | Archive leaderboard | report |
| Sarcasm Detection | SARC (pol-unbal) | Bag-of-Words | Avg F1 | 27.0 | #1 of 1 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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