Analyzing Public Sentiment on COVID-19 Using TF-IDF and K-Nearest Neighbors (K-NN) on Twitter Data - ., Arip; Kalifia, Dina (KH. A. Wahab Hasbullah University, 2024)
The coronavirus outbreak that occurred in almost all countries in the world has had an impact not only on the health sector, but also on other sectors such as tourism, finance, transportation, etc. This has given rise to various kinds of sentiments from the public with the emergence of the coronavirus as a trending topic on social media Twitter. Twitter was chosen by the public because it can disseminate information in real time and can see the market's reaction quickly. In this study,