COVID-19 Misinformation Detection: Machine-Learned Solutions to the Infodemic.

ABSTRACT:

Background

The volume of COVID-19-related misinformation has long exceeded the resources available to fact checkers to effectively mitigate its ill effects. Automated and web-based approaches can provide effective deterrents to online misinformation. Machine learning-based methods have achieved robust performance on text classification tasks, including potentially low-quality-news credibility assessment. Despite the progress of initial, rapid interventions, the enormity of COVID-19-related misinformation continues to overwhelm fact checkers. Therefore, improvement in automated and machine-learned methods for an infodemic response is urgently needed.

Objective

The aim of this study was to achieve improvement in automated and machine-learned methods for an infodemic response.<

SUBMITTER: Kolluri N 

PROVIDER: S-EPMC9987189 | biostudies-literature | 2022 Jul-Dec

REPOSITORIES: biostudies-literature