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
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 spatial and temporal
characteristics. Further, categorical classification was performed using
transformer models to assign categories for the misinformation tweets.
Word2Vec+BiLSTM was the best model for misinformation classification, with an
F1-score of 0.92. The US had the highest proportion of misinformation tweets
(58.02%), followed by the UK (10.38%) and India (7.33%). Disgust, anticipation,
and anger were associated with an increased prevalence of misinformation
tweets. Disgust was the predominant emotion associated with misinformation
tweets in the US, while anticipation was the predominant emotion in India. For
India, the misinformation rate exhibited a lead relationship with vaccination,
while in the US it lagged behind vaccination. Our study deciphered that
emotions acted as differential carriers of misinformation across geography and
time. These carriers can be monitored to develop strategic interventions for
countering misinformation, leading to improved public health.