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.gitattributes

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README.md

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----
-annotations_creators:
-- crowdsourced
-- expert-generated
-language_creators:
-- crowdsourced
-language:
-- tr
-license:
-- 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.".
-
-There are 492.782 labeled sentences. %10 of them used for testing.
-
-# Türkçe Duygu Analizi Veriseti
-Bu veriseti , farklı kaynaklardan derlenmiş pozitif , negatif ve nötr sınıflardan örnekler içerir. Bir çok verisetinde sadece pozitif ve negatif bulunur. Fakat kullanıcı input'u nötr olabilir. Bu tarz durumlar için türkçe bir dataset bulmakta zorlandım. Dolayısıyla , 3 sınıftan oluşan bu dataseti oluşturdum. Pozitif ve negatif örnekleri aldığın kaynaklar referans kısmında listelenmiştir. Nötr cümleler ise wikipedia datasından alınmıştır. Ek olarak bazı rastgele inputlar nötr olarak eklenmiştir. Örneğin: "Lorem ipsum dolor sit amet.".
-
-There are 492.782 labeled sentences. %10 of them used for testing.
-
-# References 
-- https://www.kaggle.com/burhanbilenn/duygu-analizi-icin-urun-yorumlari
-- https://github.com/fthbrmnby/turkish-text-data
-- https://www.kaggle.com/mustfkeskin/turkish-wikipedia-dump
-- https://github.com/ezgisubasi/turkish-tweets-sentiment-analysis
-- http://humirapps.cs.hacettepe.edu.tr/

train.csv → winvoker--turkish-sentiment-analysis-dataset/csv-test.parquet

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winvoker--turkish-sentiment-analysis-dataset/csv-train.parquet

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