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Webis Trigger Warning Corpus 2023

<p><strong>Abstract&nbsp; &nbsp;</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&nbsp;Trigger Warning Corpus (WTWC), the first&nbsp;dataset of 1 million fanfiction works from the&nbsp;Archive of our Own with up to 36 different&nbsp;warnings per document. To provide a reliable catalog of trigger warnings, we carefully&nbsp;mapped institutionally-recommended trigger&nbsp;warnings against the millions of free-form tags&nbsp;assigned by fanfiction authors and organized&nbsp;them into the first comprehensive taxonomy of&nbsp;trigger warnings.</p> <p>&nbsp;</p> <p><strong>Code for dehydration&nbsp;&nbsp;&nbsp;</strong>https://github.com/webis-de/ACL-23</p> <p>&nbsp;</p> <p><strong>Cite&nbsp; &nbsp;</strong></p> <pre>@InProceedings{wiegmann:2023a, address = {Toronto, Canada}, author = {Matti Wiegmann and Magdalena Wolska and Christopher Schr{\&quot;{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>&nbsp;</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

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