Google Maps stopped being a reliable way to find good restaurants a long time ago. Any time in my city when I see a place with a high rating and suspiciously large number of reviews, searching for "five stars" in the reviews inevitably finds customers helpfully mentioning that they got free food in exchange. I've even seen places advertise the bribe openly on Maps. It would be trivial to detect this and punish offenders, but Google chooses not to.
I've been mulling over starting a boutique social network focused on location reviews with real life friends exclusively.
I think Netflix realized that reducing ratings to a simple thumbs up/down was a bad idea after all. A while back they introduced the ability to give double thumbs up which, if you can treat non-rating as a kind of rating, means they're using a four point scale: thumbs down, no rating, thumbs up, double thumbs up.
Netflix are right that 5-stars is too many, it translates to a 6 point scale when you include non-rating, and I don't think there is a consistent view on what "3 stars" means, and how it's different to either 4 stars or 2 stars ( depending on the person ).
For some people 3 stars is an acceptable rating, closer to 4 stars than 2 stars. For others, 3 stars is a bad rating, closer to 2 stars than 5 stars. And for others still, it doesn't give signal beyond what a non-rating would be, it's "I don't have a strong opinion about this".
Effectively chopping out the 3-star rating, leaves it with a better a scale of:
- Excellent, I want to put effort into seeking out similar content
- Fine, I'd be happy to watch more like it
- Bad, I didn't enjoy this
- Terrible, I want to put effort into avoiding this
With the implicit:
- I have no opinion on this
But since it's not a survey, it doesn't need to be explicit, that's coded into not rating it instead.
These are comparable to a 5 point Likert scale:
"I enjoy this content"
- Strongly agree
- Agree
- Neither Agree nor Disagree
- Disagree
- Strongly Disagree
The current Netflix scale effectively merges Disagree and Strongly Disagree, and for matters of taste that may well be fine.
It would be interesting to conduct social science with a similar scale with merged Disagree and Strongly disagree to see if that gave it any better consistency.
When given a 5-star choice “very bad/bad/ok-ish/good/very good”, I rarely pick one of the extremes.
I suspect there are others who rarely click “bad” or “good”.
Because of that, I think you first need to train a model on scaling each user’s judgments to a common unit. That likely won’t work well for users that you have little data on.
So, it’s quite possible that a ML model trained on a 3-way choice “very bad or bad/OK-ish/good or very good” won’t do much worse than on given the full 5-way choice.
I think it also is likely that users will be less likely to click on a question the more choices you give them (that certainly is the case if the number of choices gets very high as in having to separately rate a movie’s acting, scenery, plot, etc)
Combined, that may mean given users less choice leads to better recommendations.
I’m sure Netflix has looked at their data well and knows more about that, though.
I apply my own meaning to the 5-star rating, and find it to work really well:
1 = The movie was so bad I didn't/couldn't finish watching it.
2 = I watched it all, but didn't enjoy it and wouldn't recommend it to anyone.
3 = The movie was worth watching once, but I have no interest in watching it again.
4 = I enjoyed it, and would enjoy watching it again if it came up. I'd recommend it.
5 = a great movie -- I could enjoy watching it many times, and highly recommend it.
> The current Netflix scale effectively merges Disagree and Strongly Disagree, and for matters of taste that may well be fine.
I'm a bit skeptical about this.
To me there's a big difference between "This didn't spark joy" and "I actively hated this": I might dislike a poorly-made sequel of a movie I previously enjoyed, but I never ever want to see baby seals getting clubbed to death again.
Every series has that one bad episode you have to struggle through during a full rewatch. Very few series have an episode bad enough that it'll make you quit watching the series entirely, and ruin any chance at a future rewatch.
Most of the Final Fantasy games have been like that, which is why I've (most of the time) been a fan since since FF4/2. I can't remember how many times I've been turned off by a game when it starts with the protagonist being woken up by his mom, followed by endless wandering around town.
That's exactly the kind of study routine that's proven to lead to mastery of the material (understanding, not just memorizing). Starting from there and with a few tweaks you've got yourself a Zettelkasten.
In the back of mind I knew it wasn't so, but I had been holding onto the belief that surely I could discern between human and bot, and that bots weren't a real issue where I spent my time anyway. But no. We're at a point where any anonymous public comment is possibly an impersonation. And eventually that "possibly" will have to replaced with "most likely".
I don't know what the solution is or if there even is one.
There isn't. Not only LLMs are good enough to fool humans like this, but they have been that for quite a while now with the right prompting. A large number of readily available open weights models can do this, so even if large providers were to crack down on this kind of use, it's still easy to run the model locally to generate such content. The cat is well and truly out of the bag.
He says in the video that YouTube is the only exception to the exclusivity clause, meaning the couldn't also publish to Float Plane or other similar platforms.
I use their products daily both professionally and personally, mostly Designer and Publisher. Coming from someone who also used to use Adobe products, the affinity suite meets my needs almost perfectly. There are some times when I sorely miss a feature, like bitmap tracing and proper vector brushes in Designer and variable spread sizes in Publisher. That said, if you're going to pay for software, they're 100% worth the price.
I think this is good use for microblogging platforms like Mastodon and the others, to which you can link to from within your blog. If you've written a lot of mini-posts[1] that fit a theme you can edit them together into larger blog post eventually. If you have complete control over your website you could even feature some of your most recent or popular mini-posts on your front page.
[1] I don't know what the best term is to describe theses kinds of posts that distinguishes them from long form blog posts. What do people do on Mastodon--toot? I'm just going with mini-post for now.
I've been mulling over starting a boutique social network focused on location reviews with real life friends exclusively.