open-source-ml-datasets/imdb

https://dagshub.com/Sookeyy-12/imdb

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: 84.13 MB
• Size of the generated dataset: 133.23 MB
• Total amount of disk used: 217.35 MB

Dataset Summary

Large Movie Review Dataset. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well.

Citation

@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}
}

Prerequisite

None

License

other

Additional Information

Dataset Structure

Data Instances

plain_text

• Size of downloaded dataset files: 84.13 MB
• Size of the generated dataset: 133.23 MB
• Total amount of disk used: 217.35 MB An example of 'train' looks as follows.

{
    "label": 0,
    "text": "Goodbye world2\n"
}

Data Fields

The data fields are the same among all splits.

plain_text

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

Data Splits

name	train	unsupervised	test
plain_text	25000	50000	25000