hdvr

It's an interesting problem. If most of the votes concentrate on the first submission, I wouldn't bother including subsequent submissions in the model. However if this is not the case (as in your example), you could actually include the past voting sequence, submission times, and domain, as predictors. In your example, the 800 votes might then (ideally) correspond to a better time slot and source/domain than the first single vote.

It seems predicting the score directly (regression) is almost impossible without considering the associated domain. E.g. headlines with the letters GPT in it from openai.com, get an order of magnitude more votes than similar headlines from other sites.

A few years ago, on my birthday, I quickly checked the visitor stats for a little side project I had started (r-exercises.com). Instead of the usual 2 or 3 live visitors, there were hundreds. It looked odd to me—more like a glitch—so I quickly returned to the party, serving food and drinks to my guests.

Later, while cleaning up after the party, I remembered the unusual spike in visitors and decided to check again. To my surprise, there were still hundreds of live visitors. The total visitor count for the day was around 10,000. After tracking down the source, I discovered that a really kind person had shared the directory/landing page I had created just a few days earlier—right here on Hacker News. It had made it to the front page, with around 200 upvotes and 40 comments: https://news.ycombinator.com/item?id=12153811

For me, the value of hitting the HN front page was twofold. First, it felt like validation for my little side project, and it encouraged me to take it more seriously (despite having a busy daily schedule as a freelance data scientist). But perhaps more importantly, it broadened my horizons and introduced me to a whole new world of information, ideas, and discussions here on HN.

Thank you HN for this wonderful birthday gift!

Ok, thank you for pointing that out.