코로나19 부스터샷의 인식에 대한 텍스트 네트워크 분석: 소셜미디어 데이터를 활용하여

Text Network Analysis of COVID-19 Booster Shots: using Social Media Data

Purpose: The purpose of this study is to analyze YouTube on COVID-19 booster shots to understand users’ perceptions of booster shots and to conduct keyword and network analysis. Methods: The social media network analysis was conducted using NetMiner 4.5 to understand what YouTube users are interested in when it comes to booster shots. Data were collected from 1 September 2021 to 31 August 2022. Results: After pre-processing the data, 632 videos and 13,497 comments were collected. The most common keywords in the 100 most viewed videos were: ‘prevention’, ‘omicron’, ‘infection’, ‘effect’ and ‘confirmation’. In the 100 most ‘liked’ comments, the most frequent keywords were ‘forced’, ‘side effects’, ‘people’. A keyword network analysis of the top 100 most viewed videos shows that the word ‘vaccine’ is associated with the following words ‘add’, ‘booster’, ‘effect’. On the other hand, a keyword network analysis of 100 comments with a high number of ‘liked’ would show that the keyword ‘vaccine’ is associated with the following keywords ‘side effects’, ‘risk’, ‘death’, ‘fear’. Conclusion: Based on these results, text mining methods on social media can help to identify public needs, sentiments, and perceptions and formulate health communication strategies during an emerging infectious disease crisis.