SNSMiner_COVAC: Analyzing COVID-19 vaccination for safety surveillance

Abstract COVID-19 is a serious threat to the socio-economic and human health worldwide. In Korea, the COVID-19 vaccine approved by the Ministry of Food and Drug Safety is being administered sequentially. We are interested in safety and adverse events and the effectiveness of the vaccine. In this study, use the comments of Naver, the largest social platform in Korea, to secure consumer sentiment information about vaccines and understand the change in Korean public sentiment in the first half of 2021 for each vaccine based on the analysis pipeline (SNSMiner_COVAC).We investigated the Korean public response to COVID-19 vaccination on social media from November 30, 2021, to January 31, 2022. We collected comments related to COVID-19 vaccination using the Korean words for "COVID-19 vaccination" as keywords.Out of 329,559 comments, 240,322 were analyzed after preprocessing. We developed 3 lexicons (stopword, sentiment word, and a custom word related to COVID-19) for Korean natural language processing. Furthermore, we extracted five clusters, such as symptoms, side effects, vaccine hesitancy, pro-vaccination, and infectious disease control policy, through network analysis. As a result of sentiment analysis, negative public opinion was prominent even after the commencement of phased recovery of daily life. It is observed that public's expectations, disappointments, and fears about vaccination still exist.We expect that this study can be used as a data source for effective management policies for newly developed vaccinations.