Create README.md

README.md

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+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- found
+languages:
+- da
+licenses:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: AngryTweets
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- sentiment-classification
+---
+
+# Dataset Card for DKHate
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Paper:** https://aclanthology.org/2021.nodalida-main.53/
+- **Direct Download**: https://danlp-downloads.alexandra.dk/datasets/game_tweets.zip
+
+### Dataset Summary
+
+This dataset consists of anonymised Danish Twitter data that has been annotated for sentiment analysis through crowd-sourcing. All credits go to the authors of the following paper, who created the dataset: 
+
+[Pauli, Amalie Brogaard, et al. "DaNLP: An open-source toolkit for Danish Natural Language Processing." Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). 2021](https://aclanthology.org/2021.nodalida-main.53/)
+
+### Supported Tasks and Leaderboards
+
+This dataset is suitable for sentiment analysis.
+
+### Languages
+
+This dataset is in Danish.
+
+## Dataset Structure
+
+### Data Instances
+
+Every entry in the dataset has a tweet and an associated label.
+
+### Data Fields
+
+An entry in the dataset consists of the following fields:
+- `text` (`str`): The tweet content.
+- `label` (`str`): The label of the `text`. Can be "positiv", "neutral" or "negativ" for positive, neutral and negative sentiment, respectively.
+
+### Data Splits
+
+A `train` and `test` split is available, with the test split being 30% of the dataset, randomly sampled in a stratified fashion. There are 2,437 tweets in the training split and 1,047 in the test split.
+
+## Additional Information
+
+### Dataset Curators
+
+The collection and annotation of the dataset is solely due to the authors of [the original paper](https://aclanthology.org/2021.nodalida-main.53/): Amalie Brogaard Pauli, Maria Barrett, Ophélie Lacroix and Rasmus Hvingelby. The tweets have been anonymised by [@saattrupdan](https://github.com/saattrupdan).
+
+### Licensing Information
+
+The dataset is released under the CC BY 4.0 license.
+
+### Citation Information
+
+```
+@inproceedings{pauli2021danlp,
+  title={DaNLP: An open-source toolkit for Danish Natural Language Processing},
+  author={Pauli, Amalie Brogaard and Barrett, Maria and Lacroix, Oph{\'e}lie and Hvingelby, Rasmus},
+  booktitle={Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)},
+  pages={460--466},
+  year={2021}
+}
+```
+
+### Contributions
+
+Thanks to [@saattrupdan](https://github.com/saattrupdan) for adding this dataset to the Hugging Face Hub.