5 ms·

Netflix are hiring professional binge-watchers to rate and review their shows

18 points by randomerr 9y ago

fenwick67 9y ago
> The streaming giant have some highly-anticipated new releases coming out in April, including Jaws, Knocked Up and The Blues Brothers . I guess 40-year-old movies are considered "new releases"
- neverminder 9y ago
  Well, if (re)mastered in 4K HDR, otherwise not so much.
overcast 9y ago
Amazing considering they reset the ratings of all the millions of binge watchers they already had. That stupid thumbs up, and thumbs down nonsense wouldn't have been bad if it retroactively gave a thumbs up to anything you rate 3 or higher. Yet here I am, re-rating movies/shows I've already done.
- BoiledCabbage 9y ago
  But I think that's the point asking people to rate with stars, they behave differently than asking if they liked/didn't. People are more likely to highly rate a high brow period piece they didn't enjoy than give it a thumbs up. So there is no translating old data to new. Hence why they need fresh ratings. They want the thumbs ups for low brow tv shows or comedies that people enjoy.
  - overcast 9y ago
    Thing is, the ratings weren't just a number of stars. They were clearly categorized in a way that made sense when you based it on the language, and not just a number value. 1. Hated it 2. Didn't like it 3. Liked it 4. Really Like it 5. Loved it Now I have to decide whether I loved it or hated it. Which is rare to be at either extreme.
    - astrodust 9y ago
      The problem with star ratings, and this has plagued star rating systems since their introduction, is different people have different rules. There's the 1/5-crowd where they either love it or hate it, and the 3-everything crowd where everything's just meh. There's also those that "save" their 5s for their absolute favourites, and only hand out 4s save for special occasions. If they had a system like "like/dislike" for preference data plus an additional "I hate this, do not show anything like it ever again" and another akin to "I love this, I will cancel my subscription if you don't renew it" you'd get better data. Some rating systems have a "super like" which you could dole out in limited quantities. Maybe Netflix needs one!
      - overcast 9y ago
        I don't see that as a problem, since the rating system was tailoring content for YOU. So whatever your rule set you decided to use for your rating, you would continue to do so in the future, and it would recommend based on that. That star rating you used to see for a movie, that was what Netflix determined YOU would rate the movie if you saw it. Not what everyone else cumulatively rated it.
        astrodust 9y ago
        The problem is normalizing rating data that's all wonky like this to try and tease out any meaningful patterns.
      - entropie 9y ago
        Well these days with ML there should be a way to get around the 5 star problem. I recently learned, think it was on the HN frontpage, that netflix uses ML to show different preview images of movies to difference audiences. (Like, iam a male and see more womans and more skin)
      - ssalka 9y ago
        It's tough to capture subjective features of data - like what a user means by rating something 4 stars - since the interpretation of each star value could mean something different to each user. But there is a (somewhat) simple solution - instead of presuming to know how to map stars to thumbs up/down for every user, let each user specify how the mapping would occur. The easiest way to go about this would be to just put 5 stars on the screen, and a toggle below each to indicate what values should map to what (eg 1,2 = thumb down; 3 = no rating; 4,5 = thumb up), and then apply the thumb ratings to everything the user has previously rated with stars. Maybe have the above settings as the default, and let the user tweak to their liking (eg, make 3 = thumb up). Boom, everyone gets their ratings migrated with little to no hassle.
sct202 9y ago
I hope they make their ratings better with this, b/c all the ratings on Netflix are so bad at predicting what I like. I usually end up searching by title or going with what's popular.
bfuller 9y ago
If anyone from Netflix is reading this and wants a 5 star binge watcher on the team just check out my profile named Big Dick Willy I am sure you will see I am qualified.
xkcd-sucks 9y ago
When alcoholics rate booze, 40s and bumwine come out on top

18 points by randomerr 9y ago

> The streaming giant have some highly-anticipated new releases coming out in April, including Jaws, Knocked Up and The Blues Brothers . I guess 40-year-old movies are considered "new releases"

neverminder 9y ago
Well, if (re)mastered in 4K HDR, otherwise not so much.

overcast 9y ago

Amazing considering they reset the ratings of all the millions of binge watchers they already had. That stupid thumbs up, and thumbs down nonsense wouldn't have been bad if it retroactively gave a thumbs up to anything you rate 3 or higher. Yet here I am, re-rating movies/shows I've already done.

BoiledCabbage 9y ago
But I think that's the point asking people to rate with stars, they behave differently than asking if they liked/didn't. People are more likely to highly rate a high brow period piece they didn't enjoy than give it a thumbs up. So there is no translating old data to new. Hence why they need fresh ratings. They want the thumbs ups for low brow tv shows or comedies that people enjoy.
- overcast 9y ago
  Thing is, the ratings weren't just a number of stars. They were clearly categorized in a way that made sense when you based it on the language, and not just a number value. 1. Hated it 2. Didn't like it 3. Liked it 4. Really Like it 5. Loved it Now I have to decide whether I loved it or hated it. Which is rare to be at either extreme.
  - astrodust 9y ago
    The problem with star ratings, and this has plagued star rating systems since their introduction, is different people have different rules. There's the 1/5-crowd where they either love it or hate it, and the 3-everything crowd where everything's just meh. There's also those that "save" their 5s for their absolute favourites, and only hand out 4s save for special occasions. If they had a system like "like/dislike" for preference data plus an additional "I hate this, do not show anything like it ever again" and another akin to "I love this, I will cancel my subscription if you don't renew it" you'd get better data. Some rating systems have a "super like" which you could dole out in limited quantities. Maybe Netflix needs one!
    - overcast 9y ago
      I don't see that as a problem, since the rating system was tailoring content for YOU. So whatever your rule set you decided to use for your rating, you would continue to do so in the future, and it would recommend based on that. That star rating you used to see for a movie, that was what Netflix determined YOU would rate the movie if you saw it. Not what everyone else cumulatively rated it.
      - astrodust 9y ago
        The problem is normalizing rating data that's all wonky like this to try and tease out any meaningful patterns.
    - entropie 9y ago
      Well these days with ML there should be a way to get around the 5 star problem. I recently learned, think it was on the HN frontpage, that netflix uses ML to show different preview images of movies to difference audiences. (Like, iam a male and see more womans and more skin)
    - ssalka 9y ago
      It's tough to capture subjective features of data - like what a user means by rating something 4 stars - since the interpretation of each star value could mean something different to each user. But there is a (somewhat) simple solution - instead of presuming to know how to map stars to thumbs up/down for every user, let each user specify how the mapping would occur. The easiest way to go about this would be to just put 5 stars on the screen, and a toggle below each to indicate what values should map to what (eg 1,2 = thumb down; 3 = no rating; 4,5 = thumb up), and then apply the thumb ratings to everything the user has previously rated with stars. Maybe have the above settings as the default, and let the user tweak to their liking (eg, make 3 = thumb up). Boom, everyone gets their ratings migrated with little to no hassle.

sct202 9y ago

I hope they make their ratings better with this, b/c all the ratings on Netflix are so bad at predicting what I like. I usually end up searching by title or going with what's popular.

bfuller 9y ago

If anyone from Netflix is reading this and wants a 5 star binge watcher on the team just check out my profile named Big Dick Willy I am sure you will see I am qualified.

xkcd-sucks 9y ago

When alcoholics rate booze, 40s and bumwine come out on top