The Role of the Crowd in Countering Misinformation: A Case Study of the COVID-19 Infodemic

11/11/2020
by   Nicholas Micallef, et al.
4

Fact checking by professionals is viewed as a vital defense in the fight against misinformation.While fact checking is important and its impact has been significant, fact checks could have limited visibility and may not reach the intended audience, such as those deeply embedded in polarized communities. Concerned citizens (i.e., the crowd), who are users of the platforms where misinformation appears, can play a crucial role in disseminating fact-checking information and in countering the spread of misinformation. To explore if this is the case, we conduct a data-driven study of misinformation on the Twitter platform, focusing on tweets related to the COVID-19 pandemic, analyzing the spread of misinformation, professional fact checks, and the crowd response to popular misleading claims about COVID-19. In this work, we curate a dataset of false claims and statements that seek to challenge or refute them. We train a classifier to create a novel dataset of 155,468 COVID-19-related tweets, containing 33,237 false claims and 33,413 refuting arguments.Our findings show that professional fact-checking tweets have limited volume and reach. In contrast, we observe that the surge in misinformation tweets results in a quick response and a corresponding increase in tweets that refute such misinformation. More importantly, we find contrasting differences in the way the crowd refutes tweets, some tweets appear to be opinions, while others contain concrete evidence, such as a link to a reputed source. Our work provides insights into how misinformation is organically countered in social platforms by some of their users and the role they play in amplifying professional fact checks.These insights could lead to development of tools and mechanisms that can empower concerned citizens in combating misinformation. The code and data can be found in http://claws.cc.gatech.edu/covid_counter_misinformation.html.

READ FULL TEXT

page 1

page 7

page 9

research
10/17/2020

ArCOV19-Rumors: Arabic COVID-19 Twitter Dataset for Misinformation Detection

In this paper we introduce ArCOV19-Rumors, an Arabic COVID-19 Twitter da...
research
08/19/2022

Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?

Fact-checking is one of the effective solutions in fighting online misin...
research
12/14/2022

Comparative Analysis of Engagement, Themes, and Causality of Ukraine-Related Debunks and Disinformation

This paper compares quantitatively the spread of Ukraine-related disinfo...
research
04/26/2022

CoVERT: A Corpus of Fact-checked Biomedical COVID-19 Tweets

Over the course of the COVID-19 pandemic, large volumes of biomedical in...
research
03/30/2020

Analysing the Extent of Misinformation in Cancer Related Tweets

Twitter has become one of the most sought after places to discuss a wide...
research
01/20/2021

VoterFraud2020: a Multi-modal Dataset of Election Fraud Claims on Twitter

The wide spread of unfounded election fraud claims surrounding the U.S. ...
research
03/11/2023

Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation

The spread of online misinformation threatens public health, democracy, ...

Please sign up or login with your details

Forgot password? Click here to reset