Data Exploration and Classification of News Article Reliability: Deep Learning Study.

ABSTRACT:

Background

During the ongoing COVID-19 pandemic, we are being exposed to large amounts of information each day. This "infodemic" is defined by the World Health Organization as the mass spread of misleading or false information during a pandemic. This spread of misinformation during the infodemic ultimately leads to misunderstandings of public health orders or direct opposition against public policies. Although there have been efforts to combat misinformation spread, current manual fact-checking methods are insufficient to combat the infodemic.

Objective

We propose the use of natural language processing (NLP) and machine learning (ML) techniques to build a model that can be used to identify unreliable news articles online.

Methods

First, we preprocessed the ReCOVery da

SUBMITTER: Zhan K 

PROVIDER: S-EPMC9516811 | biostudies-literature | 2022 Jul-Dec

REPOSITORIES: biostudies-literature