Webis Trigger Warning Corpus 2023
<p><strong>Abstract </strong>A trigger warning or a content warning is intended to enable individuals to make an informed decision about whether to expose themselves to potentially distressing content. We introduce trigger warning assignment as a multilabel classification task and create the Webis Trigger Warning Corpus (WTWC), the first dataset of 1 million fanfiction works from the Archive of our Own with up to 36 different warnings per document. To provide a reliable catalog of trigger warnings, we carefully mapped institutionally-recommended trigger warnings against the millions of free-form tags assigned by fanfiction authors and organized them into the first comprehensive taxonomy of trigger warnings.</p> <p> </p> <p><strong>Code for dehydration </strong>https://github.com/webis-de/ACL-23</p> <p> </p> <p><strong>Cite </strong></p> <pre>@InProceedings{wiegmann:2023a, address = {Toronto, Canada}, author = {Matti Wiegmann and Magdalena Wolska and Christopher Schr{\"{o}}der and Ole Borchardt and Benno Stein and Martin Potthast}, booktitle = {Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)}, month = jul, publisher = {Association for Computational Linguistics}, title = {{Trigger Warning Assignment as a Multi-Label Document Classification Problem}}, year = 2023 } </pre> <p> </p>
ShareScore
44/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 4