# Utilising Weak Supervision to Create S3D: A Sarcasm Annotated Dataset
This is the repository for the S3D dataset published at EMNLP 2022. The dataset can help build sarcasm detection models.

# SAD
The SAD dataset is our gold standard dataset of tweets labelled for sarcasm. These tweets were scraped by observing a '#sarcasm' hashtag and then manually annotated by three annotators.
There are a total of 1170 pairs of a sarcastic and non-sarcastic tweets which were both posted by the same user, resulting in a total of 2340 tweets annotated for sarcasm.
These tweets can be accessed by using the Twitter API so that they can be used for other experiments.

# Data Fields
- Tweet ID: The ID of the labelled tweet
- Label: A label to denote if a given tweet is sarcastic

# Data Splits
- Train: 1638
- Valid: 351
- Test: 351
task_categories:text-classification annotations_creators:Jordan Painter, Diptesh Kanojia multilinguality:monolingual size_categories:1K<n<10K source_datasets:original language:en license:cc-by-sa-4.0 region:us
{"annotations_creators": ["Jordan Painter, Diptesh Kanojia"], "language": ["en"], "license": ["cc-by-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "pretty_name": "Utilising Weak Supervision to create S3D: A Sarcasm Annotated Dataset"}
TAGS
#task_categories-text-classification #annotations_creators-Jordan Painter, Diptesh Kanojia #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-cc-by-sa-4.0 #region-us 

# Utilising Weak Supervision to Create S3D: A Sarcasm Annotated Dataset
This is the repository for the S3D dataset published at EMNLP 2022. The dataset can help build sarcasm detection models.

# SAD
The SAD dataset is our gold standard dataset of tweets labelled for sarcasm. These tweets were scraped by observing a '#sarcasm' hashtag and then manually annotated by three annotators.
There are a total of 1170 pairs of a sarcastic and non-sarcastic tweets which were both posted by the same user, resulting in a total of 2340 tweets annotated for sarcasm.
These tweets can be accessed by using the Twitter API so that they can be used for other experiments.

# Data Fields
- Tweet ID: The ID of the labelled tweet
- Label: A label to denote if a given tweet is sarcastic

# Data Splits
- Train: 1638
- Valid: 351
- Test: 351
# Utilising Weak Supervision to Create S3D: A Sarcasm Annotated Dataset
This is the repository for the S3D dataset published at EMNLP 2022. The dataset can help build sarcasm detection models. # SAD
The SAD dataset is our gold standard dataset of tweets labelled for sarcasm. These tweets were scraped by observing a '#sarcasm' hashtag and then manually annotated by three annotators.
There are a total of 1170 pairs of a sarcastic and non-sarcastic tweets which were both posted by the same user, resulting in a total of 2340 tweets annotated for sarcasm.
These tweets can be accessed by using the Twitter API so that they can be used for other experiments. # Data Fields
- Tweet ID: The ID of the labelled tweet
- Label: A label to denote if a given tweet is sarcastic # Data Splits
- Train: 1638
- Valid: 351
- Test: 351
TAGS
#task_categories-text-classification #annotations_creators-Jordan Painter, Diptesh Kanojia #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-cc-by-sa-4.0 #region-us 
 # Utilising Weak Supervision to Create S3D: A Sarcasm Annotated Dataset
This is the repository for the S3D dataset published at EMNLP 2022. The dataset can help build sarcasm detection models. # SAD
The SAD dataset is our gold standard dataset of tweets labelled for sarcasm. These tweets were scraped by observing a '#sarcasm' hashtag and then manually annotated by three annotators.
There are a total of 1170 pairs of a sarcastic and non-sarcastic tweets which were both posted by the same user, resulting in a total of 2340 tweets annotated for sarcasm.
These tweets can be accessed by using the Twitter API so that they can be used for other experiments. # Data Fields
- Tweet ID: The ID of the labelled tweet
- Label: A label to denote if a given tweet is sarcastic # Data Splits
- Train: 1638
- Valid: 351
- Test: 351