Home The Significance of YouTube’s New Swarm Tool

The Significance of YouTube’s New Swarm Tool

YouTube has begun experimenting with a visualization of related videos that’s a poor knock-off of the Digg Swarm visualization tool.

NewTeeVee says it’s more fun than Digg Swarm but I think it’s less useful and actually a bit nauseating to watch. (Update: By the end of the day, it’s actually much improved.)

There’s coverage at Lifehacker, Download Squad and I discovered it at Google Operating System. It’s fun to see everyone’s slightly different take on this interesting little feature. I’ll share my perspective below, but first – try the visualization out on this video. Click the full-screen option on the bottom right of the video then click on the network icon in the bottom left. Then hold on to your lunch. There’s no full screen option on embeds off-site so you’ll have to visit a videos page on YouTube.

Here’s a quick screenshot of recommended videos based on the Zombies in Plain English video linked to above. An interesting algorithm, is it not?

My Take on This Tool

There’s a couple of things that I think are notable here.

First, the videos are different than the “related videos” in the sidebar of the YouTube page. Second, this visualization is really half-baked. What’s the biggest take-away for me here, though? Recommendation and visualization are going to be major issues in the near-term future. In a world of information overload – effective systems of visualization will be small gold-mines and effective recommendation engines will be very large gold mines. That’s why the company that made the “Plain English” videos, Common Craft, got hired to do product intro videos for Google – because visual explanation is a rare skill with big payoffs. That’s also why it’s not at all crazy that recommendation engine MyStrands has now raised more than $55 million. Recommendation and visualization are going to be key challenges for the future. More than just a neat little experiment, today’s YouTube visualization is a peak into the future. The fact that they released something so half-baked into the wild just goes to show that visualizing recommendations is easier said than done.

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