Datasets › iSarcasm
iSarcasm
iSarcasm is a dataset of tweets, each labelled as either sarcastic or non_sarcastic. Each sarcastic tweet is further labelled for one of the following types of ironic speech:
- sarcasm: tweets that contradict the state of affairs and are critical towards an addressee;
- irony: tweets that contradict the state of affairs but are not obviously critical towards an addressee;
- satire: tweets that appear to support an addressee, but contain underlying disagreement and mocking;
- understatement: tweets that undermine the importance of the state of affairs they refer to;
- overstatement: tweets that describe the state of affairs in obviously exaggerated terms;
- rhetorical question: tweets that include a question whose invited inference (implicature) is obviously contradicting the state of affairs.
For each sarastic tweet, there's also:
- an explanation, in English sentences, as to why it is sarcastic, and
- a rephrase that conveys the same meaning non-sarcastically. Both have been provided by the author of the tweet.
iSarcasm contains 4,484 tweets, out of which 777 are labelled as sarcastic and 3,707 as non-sarcastic. You'll find two files, isarcasm_train.csv and isarcasm_test.csv, each containing 80% and 20% of the examples chosen at random, respectively. Each line in a file has the format tweet_id,sarcasm_label,sarcasm_type, where sarcasm_type are only defined for sarcastic tweets, as specified above.
Source: iSarcasm
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Sarcasm Detection | iSarcasm | RoBERTa + Mutation Data Augmentation F1-Score 0.414 | UTNLP at SemEval-2022 Task 6: A Comparative Analysis of... | amirabaskohi/semeval2022-task6-sarcasm-detection +1 | 1 | Compare |
Papers archive 2025-07-28
1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 17. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| UTNLP at SemEval-2022 Task 6: A Comparative Analysis of Sarcasm Detection Using Generative-based and Mutation-based Data Augmentation | 2 | 1 | 18 Apr 2022 | not harvested |
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- iSarcasm
1 variant name, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections