Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K - 100K
License:
metadata
pretty_name: RottenTomatoes - MR Movie Review Data
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
languages:
- en
licenses:
- unknown
multilinguality:
- monolingual
task_categories:
- text-classification
task_ids:
- sentiment-classification
paperswithcode_id: mr
size_categories:
- 1K<n<10K
source_datasets:
- original
Dataset Card for "rotten_tomatoes"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: http://www.cs.cornell.edu/people/pabo/movie-review-data/
- Repository: More Information Needed
- Paper: https://arxiv.org/abs/cs/0506075
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 0.47 MB
- Size of the generated dataset: 1.28 MB
- Total amount of disk used: 1.75 MB
Dataset Summary
Movie Review Dataset. This is a dataset of containing 5,331 positive and 5,331 negative processed sentences from Rotten Tomatoes movie reviews. This data was first used in Bo Pang and Lillian Lee, ``Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales.'', Proceedings of the ACL, 2005.
Supported Tasks and Leaderboards
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
default
- Size of downloaded dataset files: 0.47 MB
- Size of the generated dataset: 1.28 MB
- Total amount of disk used: 1.75 MB
An example of 'validation' looks as follows.
{
"label": 1,
"text": "Sometimes the days and nights just drag on -- it 's the morning that make me feel alive . And I have one thing to thank for that : pancakes . "
}
Data Fields
The data fields are the same among all splits.
default
text: astringfeature.label: a classification label, with possible values includingneg(0),pos(1).
Data Splits
| name | train | validation | test |
|---|---|---|---|
| default | 8530 | 1066 | 1066 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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
@InProceedings{Pang+Lee:05a,
author = {Bo Pang and Lillian Lee},
title = {Seeing stars: Exploiting class relationships for sentiment
categorization with respect to rating scales},
booktitle = {Proceedings of the ACL},
year = 2005
}
Contributions
Thanks to @thomwolf, @jxmorris12 for adding this dataset.