Nimanthika, SKuhaneswaran, BWijeratne, A.KKumara, S2026-04-022023https://rda.sliit.lk/handle/123456789/4924This study examines social media content to identify adverse effects of COVID-19 vaccination as perceived by the public. Existing studies did not categorize tweets on vaccine adverse effects as personal experience, informative, or advice-seeking. Authors manually classified tweets into categories and used the data to train four machine learning models. LSTM algorithm yielded the highest accuracy of 90.13%. The LSTM model with GloVe embedding was determined to be most suitable. This research aims to fill a research gap and increase public awareness of COVID-19 vaccine side effects. The study highlights the importance of analyzing social media content to better understand public perception of vaccines.enExploring Public PerceptionsCOVID-19 VaccineAdverse EffectsSocial Media AnalysisBook chapterDOI: 10.4018/978-1-6684-7693-2.ch009