| license: other | |
| This is the sentiment analysis dataset based on IMDB reviews initially released by Stanford University. | |
| ``` | |
| 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. | |
| Raw text and already processed bag of words formats are provided. See the README file contained in the release for more details. | |
| ``` | |
| [Here](http://ai.stanford.edu/~amaas/data/sentiment/) is the redirection. | |
| ``` | |
| @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} | |
| } | |
| ``` |