Hacker News Reader

Comment by weatherlight | Hacker News Reader

I get where you're coming from, but no system is perfect, right? While anonymity concerns and skewed reviews might be valid points, that doesn't mean we should dismiss the whole idea. Instead, we could work on refining the system to minimize these issues, like implementing measures to protect anonymity and encouraging a more balanced representation of reviews.

Remember, sites like this are just one piece of the puzzle when making decisions. Sure, they might not be perfect, but they can provide useful insights when taken with a grain of salt. And who knows? Maybe this website could inspire a new wave of accountability and transparency in the landlord-tenant relationship, which seems like a win to me.

View on HN

Further to add to your point 'RateMyProfessors.com' as a ideas was/is good.

But I understand the way it was designed (unverified students, double ratings, correlation of positive reviews to ease of the class...) did it in.

It boils down to how well thought through the implementation is, and how well it is iterated upon.

Same with yelp.com

> But I understand the way it was designed (unverified students, double ratings, correlation of positive reviews to ease of the class...) did it in.

It's still there and being used.

Ratemyprofessor was very accurate in my experience, even more so if you're good at reading between the lines of critical comments. Knowing that positive reviews generally comes from the class being easier or negative reviews comes from stricter teaching is still useful, and hardly a severe negative imo. You just need to read what the reviews say (and don't say) and adjust accordingly.

We had something administered through my university called FAQs (Faculty Assessment Questionnaire?) that were published for students and would tell you how much time a class would take per week, etc that ended up being more useful overall. Does every university have these?

Ratemyprofessors was literally responsible for improving my college experience tenthfold.

How can you know?

Before and after using it?

Do you mean tenfold?

Maybe they actually meant it only got 1/10 better.

> but no system is perfect, right?

If your data isn't going to be exhaustive or unbiased samples you could at least show the omission rate. E.g. "there were 100 tenants in period X, 1 left a review".

Reply on news.ycombinator.com