Tracking Self-reported Symptoms and Medical Conditions on Social Media During the COVID-19 Pandemic: Infodemiological Study.

ABSTRACT:

Background

Harnessing health-related data posted on social media in real time can offer insights into how the pandemic impacts the mental health and general well-being of individuals and populations over time.

Objective

This study aimed to obtain information on symptoms and medical conditions self-reported by non-Twitter social media users during the COVID-19 pandemic, to determine how discussion of these symptoms and medical conditions changed over time, and to identify correlations between frequency of the top 5 commonly mentioned symptoms post and daily COVID-19 statistics (new cases, new deaths, new active cases, and new recovered cases) in the United States.

Methods

We used natural language processing (NLP) algorithms to identify symptom- and medical condition-re

SUBMITTER: Ding Q 

PROVIDER: S-EPMC8480398 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature