Characterizing the Emotion Carriers of COVID-19 Misinformation and Their Impact on Vaccination Outcomes in India and the United States
Ridam Pal, Sanjana S, Deepak Mahto, Kriti Agrawal, Gopal Mengi, Sargun, Nagpal, Akshaya Devadiga, Tavpritesh Sethi

TL;DR
This study analyzes the emotional content of COVID-19 misinformation tweets in India and the US, revealing how different emotions influence vaccination outcomes and suggesting targeted intervention strategies.
Contribution
It introduces a novel approach to characterizing emotion carriers in misinformation across geographies using deep learning and time series analysis.
Findings
Disgust is the main emotion in US misinformation tweets.
Anticipation dominates Indian misinformation tweets.
Misinformation rates correlate differently with vaccination in India and the US.
Abstract
The COVID-19 Infodemic had an unprecedented impact on health behaviors and outcomes at a global scale. While many studies have focused on a qualitative and quantitative understanding of misinformation, including sentiment analysis, there is a gap in understanding the emotion-carriers of misinformation and their differences across geographies. In this study, we characterized emotion carriers and their impact on vaccination rates in India and the United States. A manually labelled dataset was created from 2.3 million tweets and collated with three publicly available datasets (CoAID, AntiVax, CMU) to train deep learning models for misinformation classification. Misinformation labelled tweets were further analyzed for behavioral aspects by leveraging Plutchik Transformers to determine the emotion for each tweet. Time series analysis was conducted to study the impact of misinformation on…
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Taxonomy
TopicsMisinformation and Its Impacts · Vaccine Coverage and Hesitancy · COVID-19 epidemiological studies
