task_categories:text-classification task_ids:sentiment-classification annotations_creators:crowdsourced language_creators:found multilinguality:monolingual size_categories:100K<n<1M source_datasets:original language:ko license:cc-by-2.0 region:us
This is a movie review dataset in the Korean language. Reviews were scraped from Naver movies. The dataset construction is based on the method noted in Large movie review dataset from Maas et al., 2011.
@InProceedings{Park:2016,
  title        = "Naver Sentiment Movie Corpus",
  author       = "Lucy Park",
  year         = "2016",
  howpublished = {\\url{https://github.com/e9t/nsmc}}
}
---
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-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [Github](https://github.com/e9t/nsmc/)
- **Repository:** [Github](https://github.com/e9t/nsmc/)
- **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](https://github.com/jaketae) for adding this dataset.