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Transfer Learning for Health-related Twitter Data

Anne Dirkson, Suzan Verberne
2019 Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task   unpublished
Transfer learning is promising for many NLP applications, especially in niche domains. This paper described the systems developed by team TMRLeiden for the 2019 Social Media Mining for Health Applications (SMM4H) Shared Task. Our systems make use of stateof-the-art transfer learning methods to classify, extract and normalise adverse drug effects (ADRs) and to classify personal health mentions from health-related tweets. The code and fine-tuned models are publicly available. 1
doi:10.18653/v1/w19-3212 fatcat:ax5tuzpfk5eati2txx45zvwu6u