README.md

metadata

annotations_creators:
  - crowdsourced
language_creators:
  - found
language:
  - ko
license:
  - cc-by-2.0
multilinguality:
  - monolingual
size_categories:
  - 100K<n<1M
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
paperswithcode_id: nsmc
pretty_name: Naver Sentiment Movie Corpus
dataset_info:
  features:
    - name: id
      dtype: string
    - name: document
      dtype: string
    - name: label
      dtype:
        class_label:
          names:
            '0': negative
            '1': positive
  splits:
    - name: train
      num_bytes: 16423803
      num_examples: 150000
    - name: test
      num_bytes: 5491417
      num_examples: 50000
  download_size: 19522142
  dataset_size: 21915220

Dataset Card for Naver sentiment movie corpus

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: Github
• Repository: Github
• Paper:
• Leaderboard:
• Point of Contact:

Dataset Summary

[More Information Needed]

Supported Tasks and Leaderboards

[More Information Needed]

Languages

[More Information Needed]

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

Each instance is a movie review written by Korean internet users on Naver, the most commonly used search engine in Korea. Each row can be broken down into the following fields:

• id: A unique review ID, provided by Naver
• document: The actual movie review
• label: Binary labels for sentiment analysis, where 0 denotes negative, and 1, positive

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

@InProceedings{Park:2016,
  title        = "Naver Sentiment Movie Corpus",
  author       = "Lucy Park",
  year         = "2016",
  howpublished = {\\url{https://github.com/e9t/nsmc}}
}

Contributions

Thanks to @jaketae for adding this dataset.