metadata

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: 60691412
      num_examples: 40000
    - name: test
      num_bytes: 9913682
      num_examples: 6203
  download_size: 30237219
  dataset_size: 70605094
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

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, @cstorm125 for adding this dataset.