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Studying the Dynamics of COVID-19 Misinformation Themes using Topic Streams

Authors:
Thomas Marcoux
Esther Mead
Nitin Agarwal

Keywords: misinformation, disinformation, topic models, topic streams, COVID-19, misinfodemic, narratives

Abstract:
The COVID-19 pandemic has seen the emergence of unique misinformation narratives in various outlets, through social media, blogs, etc. This online misinformation has been proven to spread in a viral manner and has a direct impact on public safety. In an effort to improve public understanding, we curated a corpus of 543 misinformation pieces whittled down to 243 unique misinformation narratives along with independent international organizations debunking these stories. Building upon previous applications of topic modeling to COVID-19 related material, we developed a tool leveraging topic modeling to create a chronological visualization of these stories. From our corpus of misinformation stories, this tool has shown to accurately represent the ground truth. This highlights some of the mis- information narratives unique to the COVID-19 pandemic and provides a quick method to monitor and assess misinformation diffusion, enabling policy makers (such as the Arkansas Office of the Attorney General - Arkansas, USA) to identify themes to focus on for communication campaigns. To further explore the potential of topic streams in understanding online opinion, we experiment with multiple topic models and also apply our methodology to YouTube data. The principal difference between our effort and other similar efforts by Google and social media companies is that we are paying special attention to cases of misinformation and scammers that are affecting our region, while also including global cases.

Pages: 15 to 23

Copyright: Copyright (c) IARIA, 2021

Publication date: July 18, 2021

Published in: conference

ISSN: 2519-8351

ISBN: 978-1-61208-884-6

Location: Nice, France

Dates: from July 18, 2021 to July 22, 2021