%0 Journal Article
%T Analysis of Public Sentiment regarding COVID-19 Vaccines on the Social Media Platform Reddit
%A Lucien Dikla Ngueleo
%A Jules Pagna Disso
%A Armel Ayimdji Tekemetieu
%A Justin Moskola£¿ Ngossaha
%A Michael Nana Kameni
%J Journal of Computer and Communications
%P 80-108
%@ 2327-5227
%D 2024
%I Scientific Research Publishing
%R 10.4236/jcc.2024.122006
%X This study undertakes a thorough analysis of the sentiment within the <i>r/Corona-virus</i> subreddit community regarding COVID-19 vaccines on Reddit. We meticulously collected and processed 34,768 comments, spanning from November 20, 2020, to January 17, 2021, using sentiment calculation methods such as TextBlob and Twitter-RoBERTa-Base-sentiment to categorize comments into positive, negative, or neutral sentiments. The methodology involved the use of Count Vectorizer as a vectorization technique and the implementation of advanced ensemble algorithms like XGBoost and Random Forest, achieving an accuracy of approximately 80%. Furthermore, through the Dirichlet latent allocation, we identified 23 distinct reasons for vaccine distrust among negative comments. These findings are crucial for understanding the community¡¯s attitudes towards vaccination and can guide targeted public health messaging. Our study not only provides insights into public opinion during a critical health crisis, but also demonstrates the effectiveness of combining natural language processing tools and ensemble algorithms in sentiment analysis.
%K COVID-19 Vaccine
%K TextBlob
%K Twitter-RoBERTa-Base-Sentiment
%K Sentiment Analysis
%K Latent Dirichlet Allocation
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=131243