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# Dataset Card for sarcasm_headlines_multilingual
size_categories:
- 100k<n
source_datasets:
- original
- https://www.kaggle.com/datasets/rmisra/news-headlines-dataset-for-sarcasm-detection
- https://www.kaggle.com/datasets/maxscheijen/dutch-news-articles
languages:
- en
- it
- nl
multilinguality:
- multilingual
task_categories:
- text_classification
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- Repository: https://github.com/helinivan/multilingual-sarcasm-detector
### Dataset Summary
Dataset consists of news article headlines in Dutch, English and Italian. The news article headlines are both from actual news sources and sarcastic/satirical newspapers. The news article is determined sarcastic/non-sarcastic based on the news article source.
The sources of news articles are:
- The Huffington Post (en, non-sarcastic)
- The Onion (en, sarcastic)
- NOS (nl, non-sarcastic)
- De Speld (nl, sarcastic)
- Il Giornale (it, non-sarcastic)
- Lercio (it, sarcastic)
### Languages
`en`, `nl`, `it`
## Dataset Structure
### Data Instances
[Needs More Information]
### Data Fields
- article_url: str
- article_title: str
- is_sarcastic: int
- lang: str
- title_length: int |