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README.md

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----
-annotations_creators:
-- Jordan Painter, Diptesh Kanojia
-language:
-- en
-license:
-- cc-by-sa-4.0
-multilinguality:
-- monolingual
-pretty_name: 'Utilising Weak Supervision to create S3D: A Sarcasm Annotated Dataset'
-size_categories:
-- 100K<n<1M
-source_datasets:
-- original
-task_categories:
-- text-classification
----
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-
-- 
-# 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.
-
-# S3D Summary
-The S3D dataset is our silver standard dataset of 100,000 tweets labelled for sarcasm using weak supervision by our **BERTweet-sarcasm-combined** model.
-These tweets can be accessed by using the Twitter API so that they can be used for other experiments.
-S3D contains 38879 tweets labelled as sarcastic, and 61211 tweets labelled as not being sarcastic.
-# Data Fields
-- Tweet ID: The ID of the labelled tweet
-- Label: A label to denote if a given tweet is sarcastic
-
-# Data Splits
-- Train: 70,000
-- Valid: 15,000
-- Test: 15,000

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