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The COVID-19 pandemic fueled one of the most rapid vaccine developments inhistory. However, misinformation spread through online social media often leadsto negative vaccine sentiment and hesitancy. To investigate COVID-19vaccine-related discussion in social media, we conducted a sentiment analysisand Latent Dirichlet Allocation topic modeling on textual data collected from13 Reddit communities focusing on the COVID-19 vaccine from Dec 1, 2020, to May15, 2021. Data were aggregated and analyzed by month to detect changes in anysentiment and latent topics. ty analysis suggested these communities expressedmore positive sentiment than negative regarding the vaccine-related discussionsand has remained static over time. Topic modeling revealed community membersmainly focused on side effects rather than outlandish conspiracy theories.Covid-19 vaccine-related content from 13 subreddits show that the sentimentsexpressed in these communities are overall more positive than negative and havenot meaningfully changed since December 2020. Keywords indicating vaccinehesitancy were detected throughout the LDA topic modeling. Public sentiment andtopic modeling analysis regarding vaccines could facilitate the implementationof appropriate messaging, digital interventions, and new policies to promotevaccine confidence.

journal of infection and public health

Public sentiment analysis and topic modeling regarding COVID-19 vaccines  on the Reddit social media platform: A call to action for strengthening  vaccine confidence