Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
German
Size:
1K - 10K
Tags:
Sentiment Analysis
License:
File size: 1,241 Bytes
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---
language:
- de
multilinguality:
- monolingual
license: cc-by-4.0
pretty_name: SB10k
task_categories:
- text-classification
tags:
- Sentiment Analysis
size_categories:
- 1K<n<10K
configs:
- config_name: default
sep: "\t"
column_names: ["ID", "Sentiment", "Text", "Normalized", "POS-Tags", "Dependency Labels", "additional Annotations"]
data_files:
- split: train
path: "train.tsv"
- split: test
path: "test.tsv"
- split: dev
path: "dev.tsv"
---
# A Twitter corpus and benchmark resources for german sentiment analysis
### Source
The data is a snapshot from the [SB10k Dataset](https://spinningbytes.com/more/resources/).
The snapshot was made by [Oliver Guhr](https://github.com/oliverguhr/german-sentiment).
### Citation Information
[Paper](https://doi.org/10.21256/zhaw-1530)
```
@inproceedings{cieliebak2017twitter,
title={A twitter corpus and benchmark resources for german sentiment analysis},
author={Cieliebak, Mark and Deriu, Jan Milan and Egger, Dominic and Uzdilli, Fatih},
booktitle={5th International Workshop on Natural Language Processing for Social Media, Boston MA, USA, 11 December 2017},
pages={45--51},
year={2017},
organization={Association for Computational Linguistics}
}
``` |