A Case Study On The Rising Omicron Cases and Public Sentiment Analysis using Twitter Data
About the project - This paper investigates the relationship between the social media platform Twitter and the trends in the new Omicron strain of the coronavirus. It provides an extensive explorative analysis of the discourse about Omicron that was reported on Twitter. The study explores a corpus and events in temporal space using a visual analytics approach mixed with natural language tools. Using the Twitter corpus containing the keyword Omicron, the model identifies the public sentiment. These insights aid authorities in making timely decisions about the appropriate support measures that can be taken. The study uses topic modelling to analyse how the topics related to the spread of the omicron with time using an extensive corpus of tweets (generated in the month of December 2021).
Repository Contents -
- Omicron Tweet Analysis.html - HTML version of the Jupyter notebook file containing the code.