Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-classification
Languages:
Thai
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
Tags:
License:
File size: 2,036 Bytes
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---
annotations_creators:
- found
language_creators:
- found
language:
- th
license:
- lgpl-3.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: WongnaiReviews
dataset_info:
features:
- name: review_body
dtype: string
- name: star_rating
dtype:
class_label:
names:
'0': '1'
'1': '2'
'2': '3'
'3': '4'
'4': '5'
splits:
- name: train
num_bytes: 60691428
num_examples: 40000
- name: test
num_bytes: 9913686
num_examples: 6203
download_size: 16556587
dataset_size: 70605114
---
# Dataset Card for Wongnai_Reviews
## Dataset Description
- **Repository:** https://github.com/wongnai/wongnai-corpus
### Dataset Summary
The Wongnai Review dataset contains restaurant reviews and ratings, almost entirely in Thai language.
The reviews are in 5 classes ranging from 1 to 5 stars.
This dataset was featured in a Kaggle challenge https://www.kaggle.com/c/wongnai-challenge-review-rating-prediction/overview
### Languages
Thai
## Dataset Structure
### Data Fields
- review_body - text of review
- star_rating - an integer star rating (1-5) or -1 (for test)
### Data Splits
Designated train (40,000 reviews) and test (6,204) sets.
### Source Data
#### Initial Data Collection and Normalization
Data was collected by Wongnai from business reviews on their website,
and shared on GitHub and Kaggle.
### Annotations
The reviews are users' own star ratings, so no additional annotation was needed.
## Additional Information
### Dataset Curators
Contributors to original GitHub repo:
- Ekkalak Thongthanomkul
- Tanapol Nearunchorn
- Yuwat Chuesathuchon
### Licensing Information
LGPL-3.0
### Citation Information
See https://github.com/wongnai/wongnai-corpus
### Contributions
Thanks to [@mapmeld](https://github.com/mapmeld), [@cstorm125](https://github.com/cstorm125) for adding this dataset. |