SNSMiner_VAC: Analyzing vaccination based on social network service data for safety surveillance

Abstract

COVID-19 has created a major issue around the world, posing a serious threat to socioeconomic and human health, and there is still fear of new infectious diseases like this. In Korea, in response to COVID-19, the COVID-19 vaccine approved by the Ministry of Food and Drug Safety was sequentially administered to each group, raising national interest in the safety, side effects, and effectiveness of the vaccine, and securing the basis for related policies. Many attempts have been made for this. We are interested in a methodology to establish a scientific basis for how to respond to issues regarding vaccine stability due to the emergence of new infectious diseases. In this study, we use comments posted on Naver, the largest social platform in Korea, to obtain 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_VAC). We investigated the Korean public’s response to the COVID-19 vaccination on social media from November 30, 2021, to January 31, 2022. We collected comments related to the COVID-19 vaccination using the Korean words for “COVID-19 vaccination” as keywords. Of the 329,559 comments, 240,322 were analyzed after preprocessing. We developed three lexicons (stopwords, sentiment words, and custom words related to COVID-19) for Korean natural language processing. Furthermore, we extracted five clusters — including symptoms, side effects, vaccine hesitancy, pro-vaccination, and infectious disease control policy — through network analysis. The sentiment analysis revealed that negative public opinion was prominent even after the commencement of the phased recovery of daily life. From these results, we were able to automatically collect data-based information on patients’ symptoms and side effects for the new vaccine and prepare and analyze the basis for collecting public opinions about vaccination. We hope that the pipeline proposed in this study can be used as a tool to create a data source for effective management policies for vaccines being developed against the emergence of new infectious diseases.