Webis Cross-Lingual Sentiment Dataset 2010 (Webis-CLS-10)
Description
The Cross-Lingual Sentiment (CLS) dataset comprises about 800.000 Amazon product reviews in the four languages English, German, French, and Japanese.
For more information on the construction of the dataset see (Prettenhofer and Stein, 2010) or the enclosed readme files. If you have a question after reading the paper and the readme files, please contact Peter Prettenhofer.
We provide the dataset in two formats: 1) a processed format which corresponds to the preprocessing (tokenization, etc.) in (Prettenhofer and Stein, 2010); 2) an unprocessed format which contains the full text of the reviews (e.g., for machine translation or feature engineering).
The dataset was first used by (Prettenhofer and Stein, 2010). It consists of Amazon product reviews for three product categories---books, dvds and music---written in four different languages: English, German, French, and Japanese. The German, French, and Japanese reviews were crawled from Amazon in November, 2009. The English reviews were sampled from the Multi-Domain Sentiment Dataset (Blitzer et. al., 2007). For each language-category pair there exist three sets of training documents, test documents, and unlabeled documents. The training and test sets comprise 2.000 documents each, whereas the number of unlabeled documents varies from 9.000 - 170.000.
Files
Restricted
The record is publicly accessible, but files are restricted to users with access.
Request access
If you would like to request access to these files, please fill out the form below.
You need to satisfy these conditions in order for this request to be accepted:
The data may only be used for scientific research purposes. The dataset may not be redistributed or shared in part or full with any third party. You may not share your access with others or give access to the dataset to unauthorized users. Any other use is explicitly prohibited.
You are currently not logged in. Do you have an account? Log in here
Additional details
References
- Peter Prettenhofer and Benno Stein. Cross-Language Text Classification using Structural Correspondence Learning. In 48th Annual Meeting of the Association of Computational Linguistics (ACL 10), pages 1118-1127, July 2010. Association for Computational Linguistics