I would think you could use the pre-trained ML model and achieve the same result. If you really want to hack away at it, the Machine Learning course at Stanford has really good notes.
http://cs229.stanford.edu/syllabus-fall2020.htmlI just thought of logistic regression because you are doing binary classification (is the title before or after the outbreak?) and it is the simplest (and most general) way to do it. But I think it would be more interesting to do linear regression (how long has it been since lockdown?) which would analyze how the sentiments change relative to the outbreak. So maybe take the time period between -2 months and +6 months relative to lockdown and then see what role time plays in the sentiment. You could easily extend this to newspapers and what not, I am sure people have tried this before!
You can conceptually change the problem of "how did breakout affect HN titles" to "given some HN title, predict whether it's before or after breakout".