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We describe the systems developed for the WNUT-2020 shared task 2,identification of informative COVID-19 English Tweets. BERT is a highlyperformant model for Natural Language Processing tasks. We increased BERT'sperformance in this classification task by fine-tuning BERT and concatenatingits embeddings with Tweet-specific features and training a Support VectorMachine (SVM) for classification (henceforth called BERT+). We compared itsperformance to a suite of machine learning models. We used a Twitter specificdata cleaning pipeline and word-level TF-IDF to extract features for thenon-BERT models. BERT+ was the top performing model with an F1-score of 0.8713.

Dartmouth CS at WNUT-2020 Task 2: Informative COVID-19 Tweet Classification Using BERT