One of the only things that stuck with me from my statistics course at university was when the professor explained newsworthiness is (or at least should be) essentially a statistical function - the less expected an outcome is the more newsworthy it is. I think it’s fair to say citizens dying of a brain eating microbe is fairly unexpected and therefore newsworthy.
Which is surprisingly (or unsurprisingly?) similar to many approaches in ML training. We train our ability to predict the future (i.e. consequences of actions) by consuming information about things we would have mispredicted (so called novel events, or news).
The danger is that if we only consume newsworthy events, we lose sense of the baseline and start only predicting outliers everywhere. We need to consume statistics or everyday stories from a diverse group of people in addition to news.
It is, precisely for the reason GP gave. The eye-catching headlines are usually ones that tell you something that's unexpected. Sometimes because the event is unexpected, other times because the headline is massaged until the point it sounds as if the event is something unexpected.
But what are we defining newsworthy as? Your professor’s formula sounds like the formula for 24/7 news and clickbait. Shouldn’t something that is actually newsworthy be something that is highly impactful for a large amount of people?
