Movie Review Data

This page is a distribution site for movie-review data for use in sentiment-analysis experiments. Available are collections of movie-review documents labeled with respect to their overall sentiment polarity (positive or negative) or subjective rating (e.g., "two and a half stars) and sentences labeled with respect to their subjectivity status (subjective or objective) or polarity. These data sets were introduced in the following papers:

Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan, Thumbs up? Sentiment Classification using Machine Learning Techniques, Proceedings of EMNLP 2002.
Bo Pang and Lillian Lee, A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts, Proceedings of ACL 2004.
Bo Pang and Lillian Lee, Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales, Proceedings of ACL 2005.

We also have available an addtional sentiment-analysis dataset, Congressional floor-debate transcripts, with support/oppose labels.

If you have results to report on these corpora, please send email to Bo Pang and/or Lillian Lee so we can add you to our list of other papers using this data. Thanks!

Please cite the version number of the dataset you used in any publications, in order to facilitate comparison of results. Thank you.

Sentiment polarity datasets

polarity dataset v2.0 ( 3.0Mb) (includes README v2.0): 1000 positive and 1000 negative processed reviews. Introduced in Pang/Lee ACL 2004. Released June 2004.
Pool of 27886 unprocessed html files (81.1Mb) from which the polarity dataset v2.0 was derived. (This file is identical to movie.zip from data release v1.0.)
sentence polarity dataset v1.0 (includes sentence polarity dataset README v1.0: 5331 positive and 5331 negative processed sentences / snippets. Introduced in Pang/Lee ACL 2005. Released July 2005.

archive:
- polarity dataset v1.0 (2.8Mb) (includes README): 700 positive and 700 negative processed reviews. Released July 2002.
- polarity dataset v1.1 (2.2Mb) (includes README.1.1): approximately 700 positive and 700 negative processed reviews. Released November 2002. This alternative version was created by Nathan Treloar, who removed a few non-English/incomplete reviews and changing some of the labels (judging some polarities to be different from the original author's rating). The complete list of changes made to v1.1 can be found in diff.txt.
- polarity dataset v0.9 (2.8Mb) (includes a README):. 700 positive and 700 negative processed reviews. Introduced in Pang/Lee/Vaithyanathan EMNLP 2002. Released July 2002. Please read the "Rating Information - WARNING" section of the README.
- movie.zip (81.1Mb): all html files we collected from the IMDb archive.

Sentiment scale datasets

scale dataset v1.0 (includes scale data README v1.0): a collection of documents whose labels come from a rating scale. Introduced in Pang/Lee ACL 2005. Released July 2005.
original reviews for scale dataset v1.0 (includes scale data README v1.0): original reviews from which the subjective extracts in scale dataset v1.0 were extracted.

Subjectivity datasets

subjectivity dataset v1.0 (508K) (includes subjectivity README v1.0): 5000 subjective and 5000 objective processed sentences. Introduced in Pang/Lee ACL 2004. Released June 2004.
Pool of unprocessed source documents (9.3Mb) from which the sentences in the subjectivity dataset v1.0 were extracted.

The creation of this website is based upon work supported in part by the National Science Foundation (NSF) under grant no. ITR/IM IIS-0081334, IIS-0329064, CCR-0122581, and BES-0329549; SRI International under subcontract no. 03-000211 on their project funded by the Department of the Interior, National Business Center; a Cornell Graduate Fellowship in Cognitive Studies; and by an Alfred P. Sloan Research Fellowship. Any opinions, findings, and conclusions or recommendations expressed above are those of the authors and do not necessarily reflect the views of the National Science Foundation or Sloan Foundation and should not be interpreted as representing the official policies, either expressed or implied, of any sponsoring institution, the U.S. government or any other entity.

If you have any questions or comments regarding this site, please send email to Bo Pang.

NLP at Cornell