Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Sub-tasks:
sentiment-classification
Languages:
Turkish
Size:
10K - 100K
Tags:
sentiment
License:
annotations_creators: | |
- Duygu Altinok | |
language: | |
- tr | |
license: | |
- cc-by-sa-4.0 | |
multilinguality: | |
- monolingual | |
size_categories: | |
- 10K<n<100K | |
source_datasets: | |
- original | |
task_categories: | |
- text-classification | |
task_ids: | |
- sentiment-classification | |
pretty_name: BuyukSinema | |
tags: | |
- sentiment | |
dataset_info: | |
features: | |
- name: text | |
dtype: string | |
- name: label | |
dtype: | |
class_label: | |
names: | |
'0': nono | |
'1': nowatch | |
'2': horrible | |
'3': poor | |
'4': bad | |
'5': middle | |
'6': good | |
'7': great | |
'8': super | |
'9': amazing | |
splits: | |
- name: train | |
num_bytes: 46979645 | |
num_examples: 67328 | |
- name: validation | |
num_bytes: 733500 | |
num_examples: 10000 | |
- name: test | |
num_bytes: 742661 | |
num_examples: 10000 | |
download_size: 58918801 | |
data_files: | |
- split: train | |
path: movies/train-* | |
- split: validation | |
path: movies/validation-* | |
- split: test | |
path: movies/test-* | |
# 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](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!! |