Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Sub-tasks:
sentiment-classification
Languages:
Turkish
Size:
100K - 1M
License:
metadata
annotations_creators:
- crowdsourced
- expert-generated
language_creators:
- crowdsourced
languages:
- tr-TR
licenses:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: Turkish Sentiment Dataset
size_categories:
- unknown
source_datasets: []
task_categories:
- text-classification
task_ids:
- sentiment-classification
Dataset
This dataset contains positive , negative and notr sentences from several data sources given in the references. In the most sentiment models , there are only two labels; positive and negative. However , user input can be totally notr sentence. For such cases there were no data I could find. Therefore I created this dataset with 3 class. Positive and negative sentences are listed below. Notr examples are extraced from turkish wiki dump. In addition, added some random text inputs like "Lorem ipsum dolor sit amet.".