Dataset:

Task Categories: text-classification
Languages: ko
Multilinguality: monolingual
Size Categories: 100K<n<1M
Licenses: cc-by-1.0
Language Creators: found
Annotations Creators: crowdsourced
Source Datasets: original

Dataset Card for Naver sentiment movie corpus

Dataset Summary

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Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

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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

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Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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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.

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Models trained or fine-tuned on nsmc

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