The question
How did public sentiment about vaccination, masks, distancing, working from home, and sanitizer relate to state-level COVID case trends? This thesis investigated those associations using public Twitter posts.
The work behind the analysis
Collected millions of tweets and built an analytics pipeline using Kafka, Google Cloud, and BERT. The project combined data collection and engineering with sentiment analysis and interpretation.
Reading the result carefully
The analysis explores correlations in online discussion, rather than establishing that sentiment or a protective measure caused a change in case counts.