This photo provided by Netflix shows a demonstration of the service's new thumbs-up and thumbs-down rating system. Much ruckus was raised recently when Netflix announced that they would do away with their widely reviled star ratings and switch to a thumbs-up/thumbs-down system for recommendations, but a new video from the streaming giant released today clarifies the nature of this new recommendations engine. "Ratings on Netflix have never been a reflection of popularity". The story was published prematurely in error. At the heart of the problem, according to Netflix, was a misunderstanding of what the stars meant, and so it is making things more clear.
After news last month that Netflix was going to be ditching their five-star ratings for shows and movies, the company is rolling out their new rating system. We have all been misinterpreting the previous rating system, which begged you to give some thought before rating a movie or TV show. It's not a measure of overall popularity, but rather based exclusively on your individual viewing habits, behavior and ratings you've provided. This system confused many users over the years, who believed that the stars were a community aggregate of a show's overall quality, not a personal recommendation system tailored for each user. Netflix says that stars were complicated - thumbs up and thumbs down are way simpler and would help the users find the flawless match with a greater ease. Now I see any advantage to this in some ways because it does make it easier to make a decision right but I want to how good how bad it is. "They perceive it as a way to get better suggestions on Netflix, which is something they care about because it helps them find something great to watch really quickly". This score is a prediction of what Netflix thinks you may enjoy watching, based on your own unique tastes.
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Recommending videos is important to Netflix because it wants to limit the odds that subscribers become bored and cancel.
The Los Gatos, California, company previously ran a trial of the system with a select number of users, and they found a 200 per cent increase in ratings activity.