Eric Berlow and Sean Gourley: Mapping ideas worth spreading

71,074 views ・ 2013-09-18

TED


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Eric Berlow: I'm an ecologist, and Sean's a physicist,
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and we both study complex networks.
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And we met a couple years ago when we discovered
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that we had both given a short TED Talk
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about the ecology of war,
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and we realized that we were connected
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by the ideas we shared before we ever met.
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And then we thought, you know, there are thousands
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of other talks out there, especially TEDx Talks,
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that are popping up all over the world.
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How are they connected,
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and what does that global conversation look like?
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So Sean's going to tell you a little bit about how we did that.
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Sean Gourley: Exactly. So we took 24,000 TEDx Talks
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from around the world, 147 different countries,
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and we took these talks and we wanted to find
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the mathematical structures that underly
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the ideas behind them.
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And we wanted to do that so we could see how
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they connected with each other.
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And so, of course, if you're going to do this kind of stuff,
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you need a lot of data.
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So the data that you've got is a great thing called YouTube,
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and we can go down and basically pull
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all the open information from YouTube,
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all the comments, all the views, who's watching it,
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where are they watching it, what are they saying in the comments.
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But we can also pull up, using speech-to-text translation,
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we can pull the entire transcript,
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and that works even for people with kind of funny accents like myself.
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So we can take their transcript
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and actually do some pretty cool things.
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We can take natural language processing algorithms
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to kind of read through with a computer, line by line,
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extracting key concepts from this.
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And we take those key concepts and they sort of form
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this mathematical structure of an idea.
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And we call that the meme-ome.
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And the meme-ome, you know, quite simply,
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is the mathematics that underlies an idea,
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and we can do some pretty interesting analysis with it,
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which I want to share with you now.
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So each idea has its own meme-ome,
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and each idea is unique with that,
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but of course, ideas, they borrow from each other,
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they kind of steal sometimes,
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and they certainly build on each other,
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and we can go through mathematically
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and take the meme-ome from one talk
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and compare it to the meme-ome from every other talk,
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and if there's a similarity between the two of them,
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we can create a link and represent that as a graph,
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just like Eric and I are connected.
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So that's theory, that's great.
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Let's see how it works in actual practice.
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So what we've got here now is the global footprint
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of all the TEDx Talks over the last four years
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exploding out around the world
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from New York all the way down to little old New Zealand in the corner.
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And what we did on this is we analyzed the top 25 percent of these,
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and we started to see where the connections occurred,
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where they connected with each other.
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Cameron Russell talking about image and beauty
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connected over into Europe.
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We've got a bigger conversation about Israel and Palestine
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radiating outwards from the Middle East.
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And we've got something a little broader
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like big data with a truly global footprint
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reminiscent of a conversation
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that is happening everywhere.
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So from this, we kind of run up against the limits
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of what we can actually do with a geographic projection,
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but luckily, computer technology allows us to go out
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into multidimensional space.
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So we can take in our network projection
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and apply a physics engine to this,
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and the similar talks kind of smash together,
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and the different ones fly apart,
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and what we're left with is something quite beautiful.
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EB: So I want to just point out here that every node is a talk,
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they're linked if they share similar ideas,
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and that comes from a machine reading
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of entire talk transcripts,
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and then all these topics that pop out,
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they're not from tags and keywords.
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They come from the network structure
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of interconnected ideas. Keep going.
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SG: Absolutely. So I got a little quick on that,
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but he's going to slow me down.
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We've got education connected to storytelling
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triangulated next to social media.
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You've got, of course, the human brain right next to healthcare,
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which you might expect,
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but also you've got video games, which is sort of adjacent,
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as those two spaces interface with each other.
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But I want to take you into one cluster
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that's particularly important to me, and that's the environment.
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And I want to kind of zoom in on that
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and see if we can get a little more resolution.
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So as we go in here, what we start to see,
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apply the physics engine again,
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we see what's one conversation
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is actually composed of many smaller ones.
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The structure starts to emerge
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where we see a kind of fractal behavior
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of the words and the language that we use
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to describe the things that are important to us
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all around this world.
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So you've got food economy and local food at the top,
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you've got greenhouse gases, solar and nuclear waste.
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What you're getting is a range of smaller conversations,
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each connected to each other through the ideas
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and the language they share,
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creating a broader concept of the environment.
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And of course, from here, we can go
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and zoom in and see, well, what are young people looking at?
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And they're looking at energy technology and nuclear fusion.
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This is their kind of resonance
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for the conversation around the environment.
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If we split along gender lines,
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we can see females resonating heavily
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with food economy, but also out there in hope and optimism.
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And so there's a lot of exciting stuff we can do here,
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and I'll throw to Eric for the next part.
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EB: Yeah, I mean, just to point out here,
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you cannot get this kind of perspective
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from a simple tag search on YouTube.
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Let's now zoom back out to the entire global conversation
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out of environment, and look at all the talks together.
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Now often, when we're faced with this amount of content,
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we do a couple of things to simplify it.
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We might just say, well,
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what are the most popular talks out there?
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And a few rise to the surface.
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There's a talk about gratitude.
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There's another one about personal health and nutrition.
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And of course, there's got to be one about porn, right?
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And so then we might say, well, gratitude, that was last year.
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What's trending now? What's the popular talk now?
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And we can see that the new, emerging, top trending topic
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is about digital privacy.
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So this is great. It simplifies things.
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But there's so much creative content
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that's just buried at the bottom.
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And I hate that. How do we bubble stuff up to the surface
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that's maybe really creative and interesting?
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Well, we can go back to the network structure of ideas
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to do that.
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Remember, it's that network structure
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that is creating these emergent topics,
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and let's say we could take two of them,
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like cities and genetics, and say, well, are there any talks
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that creatively bridge these two really different disciplines.
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And that's -- Essentially, this kind of creative remix
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is one of the hallmarks of innovation.
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Well here's one by Jessica Green
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about the microbial ecology of buildings.
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It's literally defining a new field.
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And we could go back to those topics and say, well,
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what talks are central to those conversations?
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In the cities cluster, one of the most central
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was one by Mitch Joachim about ecological cities,
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and in the genetics cluster,
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we have a talk about synthetic biology by Craig Venter.
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These are talks that are linking many talks within their discipline.
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We could go the other direction and say, well,
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what are talks that are broadly synthesizing
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a lot of different kinds of fields.
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We used a measure of ecological diversity to get this.
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Like, a talk by Steven Pinker on the history of violence,
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very synthetic.
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And then, of course, there are talks that are so unique
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they're kind of out in the stratosphere, in their own special place,
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and we call that the Colleen Flanagan index.
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And if you don't know Colleen, she's an artist,
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and I asked her, "Well, what's it like out there
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in the stratosphere of our idea space?"
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And apparently it smells like bacon.
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I wouldn't know.
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So we're using these network motifs
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to find talks that are unique,
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ones that are creatively synthesizing a lot of different fields,
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ones that are central to their topic,
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and ones that are really creatively bridging disparate fields.
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Okay? We never would have found those with our obsession
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with what's trending now.
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And all of this comes from the architecture of complexity,
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or the patterns of how things are connected.
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SG: So that's exactly right.
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We've got ourselves in a world
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that's massively complex,
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and we've been using algorithms to kind of filter it down
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so we can navigate through it.
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And those algorithms, whilst being kind of useful,
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are also very, very narrow, and we can do better than that,
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because we can realize that their complexity is not random.
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It has mathematical structure,
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and we can use that mathematical structure
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to go and explore things like the world of ideas
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to see what's being said, to see what's not being said,
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and to be a little bit more human
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and, hopefully, a little smarter.
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Thank you.
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(Applause)
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