Non-Pharmaceutical Intervention Discovery with Topic Modeling
arXiv:2009.13602v14 citations
Originality Synthesis-oriented
AI Analysis
This work addresses the need for efficient categorization of interventions for public health researchers, but it is incremental as it applies existing methods to new data.
The paper tackled the problem of categorizing non-pharmaceutical interventions during COVID-19 by applying topic modeling to national and international corpora, resulting in discovery of existing categories and reduced human effort.
We consider the task of discovering categories of non-pharmaceutical interventions during the evolving COVID-19 pandemic. We explore topic modeling on two corpora with national and international scope. These models discover existing categories when compared with human intervention labels while reduced human effort needed.