--- annotations_creators: - Duygu Altinok language: - tr license: - cc-by-sa-4.0 multilinguality: - monolingual size_categories: - 10K ## 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](https://huggingface.co/datasets/turkish-nlp-suite/beyazperde-all-movie-reviews), [BeyazPerde Top 300 Movie Reviews](https://huggingface.co/datasets/turkish-nlp-suite/beyazperde-top-300-movie-reviews) and [Sinefil Movie Reviews](https://huggingface.co/datasets/turkish-nlp-suite/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 rating | count | |---|---| | 1 | 5,657 | | 2 | 3,092 | | 3 | 2,172 | | 4 | 3,491 | | 5 | 7,349 | | 6 | 9,078 | | 7 | 15,647 | | 8 | 21,154 | | 9 | 10,868 | | 10 | 8,820 | | total | 87,328 | 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 | name |train|validation|test| |---------|----:|---:|---:| |BüyükSinema Movie Reviews|67328|10000|10000| ## Benchmarking This dataset is a part of [TRGLUE](https://huggingface.co/datasets/turkish-nlp-suite/TrGLUE) and [SentiTurca](https://huggingface.co/datasets/turkish-nlp-suite/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](https://github.com/turkish-nlp-suite/TrGLUE). ## Citation Coming soon!!