Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Sub-tasks:
sentiment-classification
Languages:
Turkish
Size:
100K - 1M
License:
Create README.md
Browse files
README.md
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---
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language:
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- "tr"
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tags:
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- "sentiment-analysis"
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license: "CC-BY-SA-4.0"
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datasets:
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- dataset1
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- dataset2
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metrics:
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- metric1
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- metric2
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---
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# Dataset
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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.
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# References
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- https://www.kaggle.com/burhanbilenn/duygu-analizi-icin-urun-yorumlari
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- https://github.com/fthbrmnby/turkish-text-data
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- https://www.kaggle.com/mustfkeskin/turkish-wikipedia-dump
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- https://github.com/ezgisubasi/turkish-tweets-sentiment-analysis
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- http://humirapps.cs.hacettepe.edu.tr/
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