The Evolution of Rumors on a Closed Social Networking Platform During COVID-19: Algorithm Development and Content Study.

ABSTRACT:

Background

In 2020, the COVID-19 pandemic put the world in a crisis regarding both physical and psychological health. Simultaneously, a myriad of unverified information flowed on social media and online outlets. The situation was so severe that the World Health Organization identified it as an infodemic in February 2020.

Objective

The aim of this study was to examine the propagation patterns and textual transformation of COVID-19-related rumors on a closed social media platform.

Methods

We obtained a data set of suspicious text messages collected on Taiwan's most popular instant messaging platform, LINE, between January and July 2020. We proposed a classification-based clustering algorithm that could efficiently cluster messages into groups, with each group representi

SUBMITTER: Wang AW 

PROVIDER: S-EPMC8612313 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature