Abstract
Coronavirus (COVID-19) is a rapidly emerging and spreading infectious disease. To minimize the impact caused by the virus, it is necessary to have a vaccine. However, the existence of vaccinations for the Indonesian people has caused controversy so that it invites many people to give an opinion assessment, therefore people choose social media as a place to channel their opinions. In this study, a comparison was made with an observational infoveillance study by collecting data using a Python programming script (Python Software Foundation) to display posts related to the COVID-19 vaccine on Twitter as well as quantitative and qualitative analysis to identify trends and characterize the main themes discussed by twitter users on Twitter. Indonesia. Our research collects data through social media Twitter in the period August 2020 - March 2021. In this study we combine Retrospective Observation and Sentiment Analysis, with the aim of producing periodic timeline evaluations within a predetermined time frame. In this study author found that there was an interaction & increase in positive posts due to officially reported developments, on the other hand we were quite difficult to understand the factors behind the emergence of negative posts but we made a conclusion based on the results of sentiment analysis that most of the negative posts were caused by lack of information and understanding of vaccines and vaccines. the COVID-19 outbreak itself.
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