According to Hastings, the tag underwent a survey posed to action fans, and was questioned by the taggers themselves. Netflix also engages with the community, too, if they feel a tag is experimental or possibly too vague. “That’s kind of where the emotion comes into it.” But that said, our whole point is to reflect back to the user, like ‘Hey you might be interested in these things based on what you’re watching’.” We generally think about it from a geekier perspective. “We don’t think about what we do, with tags, from much of a marketing perspective. This sounds like emotional marketing, but Hastings explained it’s more than just suit-wearing wizardry employed here. “If my team sees that a tag we’ve created is not getting any clicks, then we’ve probably got something wrong, because the titles should be compelling to you.” Obviously, the most powerful signal is did you watch any of it, and did you watch a lot of it… or all of it.”Īdding content to your queue, or something as subtle as not clicking on any titles in a given row, also adds to the information store. “Those other signals, like did you search for that genre, and did you click on some of those shows, and did you add them to your list those are different signals that we might take into account. “Watching is the most powerful signal,” Hastings explains. Netflix has been using the tagging system since 2010 Tags, in addition to information garnered from user habits, allows the company to privilege what consumers would most likely like to see. While it might appear under the “family adventure” heading for one user, it may appear as an “animated kids movie” on another. According to the company, no two profiles are alike, and that’s largely due to users’ viewing habits, the algorithm and those tags.įor instance, Hastings gave an example of the movie Tangled. This myriad of tags also allows the company to granularly personalise the service’s experience across all users. Hastings notes that “bullying” has recently been added to the phrase list, which now equates to some 50 000 individual tags. Taggers are also responsible for introducing new tags if a show introduces a new concept. Will a computer know if Stranger Things is a bildungsroman, or a critique of family structure, whether it involves supernatural forces or is set in the 1980s? Probably not. We need something to make sense of that, and tagging is how we do it,” he told Memeburn in an interview. People don’t choose shows that they love. “We could have algorithms without context, but we find that when we’ve done and tested that, people don’t make choices as quickly. Arguably, if this system didn’t exist, Netflix wouldn’t have 109-million users worldwide. This co-operation fuels the company’s recommendation engine. “The human voice to the algorithm, or the ghost in the machine, that’s basically providing the sense to what the algorithms is trying to determine,” notes Mike Hastings, Netflix’s director of enhanced content, former movie critic, and a key figure in Netflix’s tagging programme since 2008. ‘We could have algorithms without context, but… people don’t choose shows they love’ And it’s these small nuances that keep us coming back to particular shows and movies. While computers can recognise patterns and habits that form during spans of content binging, they can’t pick apart traits in works. Netflix’s algorithm works in conjunction with the tagger’s input. But as entertaining as it sounds, it’s probably one of the company’s most important roles. They then tag them with the corresponding metadata.Īt this point, you’re probably wondering why the company isn’t advertising these jobs (it does, but always receives an overwhelming response I’m told), because it sounds great.
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