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
Venues:
EMNLP | 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
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.wnut-1.17.pdf
Data
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