Surveillance of Twitter Data on COVID-19 Symptoms During the Omicron Variant Period: A Sentiment Analysis.

ABSTRACT:

Background

The global outbreak of COVID-19 has significantly impacted health care systems and has necessitated timely access to information for effective decision-making by health care authorities. Conventional methods for collecting patient data and analyzing virus mutations are resource-intensive. In the current era of rapid internet development, information on COVID-19 infections could be collected by a novel approach that leverages social media, particularly Twitter (subsequently rebranded X).

Objective

The aim of this study was to analyze the trending patterns of tweets containing information about various COVID-19 symptoms, explore their synchronization and correlation with conventional monitoring data, and provide insights into the evolution of the virus. We categoriz

SUBMITTER: Zhang K 

PROVIDER: S-EPMC12456870 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature