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Busting a move with YouTube’s choreography community

A look at how the choreography community on YouTube went big.

Head to YouTube today and you’ll notice that the logo looks a little different than usual, with the signature play button now accompanied by a group of dancers showing off their footwork. That’s because we’re taking a moment on International Choreographers Day to celebrate the rich community of choreo creators who are opening their studios to viewers around the world.

YouTube’s choreography community1 is massive in size and scope, made up of over 35,000 channels spanning 130 countries. Of these, over 180 channels have hit a million or more subscribers. One explanation for their popularity: Because most choreography videos are focused on the moves and music, they’re unaffected by language barriers and can be enjoyed by anyone, anywhere. Fans can jump smoothly from Korea’s 1Million Dance Studio to India’s Team Naach to Argentina’s Emir Abdul Gani to the US’s Matt Steffanina and, well, the list goes on and on.

But, of course, there’s far more at play than a universal understanding of what’s taking place in these videos. In addition to delivering impressive skills that make viewers want to get up and move, choreo videos often feature studio dancers who come to feel like familiar friends and deepen viewers’ connection with hit songs.

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While today’s choreography videos have a look and feel that’s instantly recognizable, it wasn’t always this way. Over the years, creators have worked to develop a distinct aesthetic that has become an artform in its own right. In this video, we unpack how we got here and why this aesthetic is so important, with insights from top choreography creators like Steffanina, Team Naach, Tim Milgram and Kyle Hanagami.

In the mood for more choreo? Check out this playlist full of global takes on some of the hottest tracks. A word of warning: You’ll want to join in.

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1To determine which channels make up the choreography community, we analyzed a variety of channel uploading activity signals including video titles, tags, and other metadata to form a representative sample set. Community stats are derived from that grouping.