Understanding the Humans Behind Online Misinformation: An Observational
Study Through the Lens of the COVID-19 Pandemic
- URL: http://arxiv.org/abs/2310.08483v2
- Date: Thu, 18 Jan 2024 11:43:52 GMT
- Title: Understanding the Humans Behind Online Misinformation: An Observational
Study Through the Lens of the COVID-19 Pandemic
- Authors: Mohit Chandra, Anush Mattapalli, Munmun De Choudhury
- Abstract summary: We conduct a large-scale observational study analyzing over 32 million COVID-19 tweets and 16 million historical timeline tweets.
We focus on understanding the behavior and psychology of users disseminating misinformation during COVID-19 and its relationship with the historical inclinations towards sharing misinformation on Non-COVID domains before the pandemic.
- Score: 12.873747057824833
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The proliferation of online misinformation has emerged as one of the biggest
threats to society. Considerable efforts have focused on building
misinformation detection models, still the perils of misinformation remain
abound. Mitigating online misinformation and its ramifications requires a
holistic approach that encompasses not only an understanding of its intricate
landscape in relation to the complex issue and topic-rich information ecosystem
online, but also the psychological drivers of individuals behind it. Adopting a
time series analytic technique and robust causal inference-based design, we
conduct a large-scale observational study analyzing over 32 million COVID-19
tweets and 16 million historical timeline tweets. We focus on understanding the
behavior and psychology of users disseminating misinformation during COVID-19
and its relationship with the historical inclinations towards sharing
misinformation on Non-COVID domains before the pandemic. Our analysis
underscores the intricacies inherent to cross-domain misinformation, and
highlights that users' historical inclination toward sharing misinformation is
positively associated with their present behavior pertaining to misinformation
sharing on emergent topics and beyond. This work may serve as a valuable
foundation for designing user-centric inoculation strategies and
ecologically-grounded agile interventions for effectively tackling online
misinformation.
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