Forecasting COVID-19 caseloads using unsupervised embedding clusters of social media posts
We present a novel approach incorporating transformer-based language models into infectious disease modelling. Text-derived features are quantified by tracking high-density clusters of sentence-level representations of Reddit posts within specific US states’ COVID-19 subreddits. We benchmark these c...
| Hauptverfasser: | , , |
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| Format: | Conference item |
| Sprache: | English |
| Veröffentlicht: |
Association for Computational Linguistics
2022
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