tmn at #SMM4H 2023: Comparing Text Preprocessing Techniques for Detecting Tweets Self-reporting a COVID-19 Diagnosis

November 01, 2023 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Anna Glazkova arXiv ID 2311.00732 Category cs.CL: Computation & Language Cross-listed cs.AI, cs.LG, cs.SI Citations 1 Venue arXiv.org Last Checked 5 months ago
Abstract
The paper describes a system developed for Task 1 at SMM4H 2023. The goal of the task is to automatically distinguish tweets that self-report a COVID-19 diagnosis (for example, a positive test, clinical diagnosis, or hospitalization) from those that do not. We investigate the use of different techniques for preprocessing tweets using four transformer-based models. The ensemble of fine-tuned language models obtained an F1-score of 84.5%, which is 4.1% higher than the average value.
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