Analysis of the Relationship between Public Sentiment on Social Media and Indonesian Covid-19 Dynamics: Analisis Hubungan Sentimen Publik di Media Sosial dengan Dinamika Covid-19 Indonesia - Nana Mulyana Maghfur; Fakhri Muhammad; Apriade Voutama (Universitas Singaperbangsa Karawang, 2021)
The bad side of the open access nature of social media is that it frees anyone to have an opinion as they please and is often accompanied by other agendas such as spreading panic, false information, fake news, hate speech and even distorting public opinion. This condition can be fatal in the pandemic era where public opinion can worsen the pandemic situation. Therefore, it is important to know whether it is true that changes in public sentiment in response to news on social media can affect the dynamics of the spread of COVID-19. We use sentiment analysis using machine learning methods to extract daily sentiment data and test its correlation with daily Covid-19 case data in Indonesia. The results of the associative hypothesis test with a Pearson correlation value of 0.151 show that public sentiment on social media towards the news of the COVID-19 variant is positively correlated with the dynamics of the daily Covid-19 cases. Therefore, the author invites all social media users, including the author himself, to be more vigilant and careful in giving opinions and accepting other people's opinions on social media.