metadata

pretty_name: IMDb
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
language:
  - en
license:
  - other
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K

Dataset Card for IMDb Movie Reviews

Dataset Description

Homepage: http://ai.stanford.edu/~amaas/data/sentiment/
Repository: More Information Needed
Paper: More Information Needed
Point of Contact: More Information Needed
Size of downloaded dataset files: More Information Needed
Size of the generated dataset: More Information Needed
Total amount of disk used: More Information Needed

Dataset Summary

This is a custom train/test/validation split of the IMDb Large Movie Review Dataset available from http://ai.stanford.edu/~amaas/data/sentiment/.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

[More Information Needed]

Dataset Structure

IMDb_movie_reviews

An example of 'train':

{
    "text": "Beautifully photographed and ably acted, generally, but the writing is very slipshod. There are scenes of such unbelievability that there is no joy in the watching. The fact that the young lover has a twin brother, for instance, is so contrived that I groaned out loud. And the "emotion-light bulb connection" seems gimmicky, too.<br /><br />I don\'t know, though. If you have a few glasses of wine and feel like relaxing with something pretty to look at with a few flaccid comedic scenes, this is a pretty good movie. No major effort on the part of the viewer required. But Italian film, especially Italian comedy, is usually much, much better than this."
    "label": 0,
}

Data Fields

The data fields are the same among all splits.

IMDb_movie_reviews

text: a string feature.
label: a classification label, with values neg (0), pos (1).

Data Splits

name	train	validation	test
IMDb_movie_reviews	36000	4000	10000

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{maas-EtAl:2011:ACL-HLT2011,
  author    = {Maas, Andrew L.  and  Daly, Raymond E.  and  Pham, Peter T.  and  Huang, Dan  and  Ng, Andrew Y.  and  Potts, Christopher},
  title     = {Learning Word Vectors for Sentiment Analysis},
  booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
  month     = {June},
  year      = {2011},
  address   = {Portland, Oregon, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {142--150},
  url       = {http://www.aclweb.org/anthology/P11-1015}
}

Contributions

[More Information Needed]