DreamDrug - A crowdsourced NER dataset for detecting drugs in darknet markets
Johannes Bogensperger, Sven Schlarb, Allan Hanbury, Gábor Recski
Abstract
We present DreamDrug, a crowdsourced dataset for detecting mentions of drugs in noisy user-generated item listings from darknet markets. Our dataset contains nearly 15,000 manually annotated drug entities in over 3,500 item listings scraped from the darknet market platform “DreamMarket” in 2017. We also train and evaluate baseline models for detecting these entities, using contextual language models fine-tuned in a few-shot setting and on the full dataset, and examine the effect of pretraining on in-domain unannotated corpora.- Anthology ID:
- 2021.wnut-1.17
- Volume:
- Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Venue:
- WNUT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 137–157
- Language:
- URL:
- https://aclanthology.org/2021.wnut-1.17
- DOI:
- 10.18653/v1/2021.wnut-1.17
- Cite (ACL):
- Johannes Bogensperger, Sven Schlarb, Allan Hanbury, and Gábor Recski. 2021. DreamDrug - A crowdsourced NER dataset for detecting drugs in darknet markets. In Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021), pages 137–157, Online. Association for Computational Linguistics.
- Cite (Informal):
- DreamDrug - A crowdsourced NER dataset for detecting drugs in darknet markets (Bogensperger et al., WNUT 2021)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2021.wnut-1.17.pdf
- Data
- DBpedia