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turkish-nlp-suite/BuyukSinema

BüyükSinema - A Large Scale Turkish Movie Reviews Sentiment Dataset Dataset Summary BüyükSinema is a Turkish movie reviews dataset of size 87K, scraped from Sinefil.com and Beyazperde.com. Hence this dataset is a superset of BeyazPerde All Movie Reviews, BeyazPerde Top 300 Movie Reviews and Sinefil Movie Reviews datasets. This is a merge of the three different datasets from two resources, hence we scaled the output stars into the range of 1-10 accordingly.… See the full description on the dataset page: https://huggingface.co/datasets/turkish-nlp-suite/BuyukSinema.

sourceHugging Facecc-by-sa-4.0updated 2y agoView on Hugging Face
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Dataset Card

BüyükSinema - A Large Scale Turkish Movie Reviews Sentiment Dataset

<img src="https://raw.githubusercontent.com/turkish-nlp-suite/.github/main/profile/buyuksinema.png" width="30%" height="30%">

Dataset Summary

BüyükSinema is a Turkish movie reviews dataset of size 87K, scraped from Sinefil.com and Beyazperde.com. Hence this dataset is a superset of BeyazPerde All Movie Reviews, BeyazPerde Top 300 Movie Reviews and Sinefil Movie Reviews datasets.

This is a merge of the three different datasets from two resources, hence we scaled the output stars into the range of 1-10 accordingly.

The star distribution is as follows:

star ratingcount
15,657
23,092
32,172
43,491
57,349
69,078
715,647
821,154
910,868
108,820
total87,328

The star distribution is quite skewed towards 7+ stars. For more information about dataset statistics, please refer to the [research paper]().

Dataset Instances

An instance looks like:

{
"text":"Mükemmelin ötesinde bir şey. Helal olsun. Devamını da isteriz artık... Emeğinize Yüreğinize Sağlık...",
"label":9
}

Data Split

nametrainvalidationtest
BüyükSinema Movie Reviews673281000010000

Benchmarking

This dataset is a part of TRGLUE and SentiTurca benchmarks, in the benchmark the subset name is TrSST-2, named according to the GLUE tasks. Also the TrGLUE and SentiTurca tasks are binary classification tasks to follow original GLUE conventions. In this repo, you can access the original star ratings if you want a challenge.

We benchmarked the transformer based model BERTurk on the binary classification task, this model achieved a 0.67 Matthews's correlation coefficient. More information can be found in the [research paper]() and benchmarking code can be found under TrGLUE Github repo.

Citation

Coming soon!!

turkish-nlp-suite/BuyukSinema · CoolFace