Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing.

ABSTRACT: We used social media data from "covid19positive" subreddit, from 03/2020 to 03/2022 to identify COVID-19 cases and extract their reported symptoms automatically using natural language processing (NLP). We trained a Bidirectional Encoder Representations from Transformers classification model with chunking to identify COVID-19 cases; also, we developed a novel QuadArm model, which incorporates Question-answering, dual-corpus expansion, Adaptive rotation clustering, and mapping, to extract symptoms. Our classification model achieved a 91.2% accuracy for the early period (03/2020-05/2020) and was applied to the Delta (07/2021-09/2021) and Omicron (12/2021-03/2022) periods for case identification. We identified 310, 8794, and 12,094 COVID-positive authors in the three periods, respectively. The

SUBMITTER: Guo M 

PROVIDER: S-EPMC10444846 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature