You need to agree to share your contact information to access this dataset
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
By requesting and downloading CoDA, the user acknowledges that the use of this dataset is restricted to research and/or academic purposes only.
Log in or Sign Up to review the conditions and access this dataset content.
CoDA Dataset
Terms of Usage
CoDA is available for access upon request. Users may submit their request using the form below, which includes the name of the user, the user’s institution, the user’s email address that matches the institution, and the purpose of usage. By requesting and downloading CoDA, the user agrees to the following: the user acknowledges that the use of this dataset is restricted to research and/or academic purposes only. A request may be declined if it does not sufficiently describe research purposes that follow the ACM Code of Ethics (https://www.acm.org/code-of-ethics). The information provided by the requesting user will not be used in any way except for sending the dataset to the user and keeping track of request history for CoDA. By requesting for the dataset, the user agrees to our collection of the provided information. This dataset shall only be used for non-profit research purposes and in a manner consistent with fair practice. Do not redistribute this dataset to others. The user should indicate the source of this dataset (found at the bottom of the page) when using or citing the data in their research or article.
Citation
If you are using the CoDA dataset, please cite the following paper accordingly:
Youngjin Jin, Eugene Jang, Yongjae Lee, Seungwon Shin, and Jin-Woo Chung. 2022. Shedding New Light on the Language of the Dark Web. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 5621–5637, Seattle, United States. Association for Computational Linguistics.
- Downloads last month
- 166