surrey-nlp/S3D

This repository contains our sarcasm annotated datasets along with notebooks to use our fine-tuned language models for our EMNLP 2022 Workshop Paper: "Utilizing Weak Supervision to Create S3D: A Sarcasm Annotated Dataset"

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Experimental

This project offers specialized datasets and pre-trained models to help you automatically detect sarcasm in social media text. It provides sets of Twitter posts, each labeled as sarcastic or not, that you can use as input. The output is a tool to improve the accuracy of understanding social media conversations. This is for researchers, data scientists, or analysts working with social media data.

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Use this if you need high-quality, pre-labeled social media text data (specifically tweets) to train or evaluate models for identifying sarcasm.

Not ideal if you need to detect sarcasm in languages other than English or in very different text formats like formal documents or long-form articles.

social-media-analysis sentiment-analysis social-listening computational-linguistics text-classification
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Jupyter Notebook

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CC-BY-SA-4.0

Last pushed

Jan 21, 2023

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