Eric Berlow: I'm an ecologist, and Sean's a physicist, and we both study complex networks. And we met a couple years ago when we discovered that we had both given a short TED Talk about the ecology of war, and we realized that we were connected by the ideas we shared before we ever met. And then we thought, you know, there are thousands of other talks out there, especially TEDx Talks, that are popping up all over the world. How are they connected, and what does that global conversation look like? So Sean's going to tell you a little bit about how we did that.
Eric Berlow: Une jam nje ekolog dhe Sean eshte nje fizikant, se bashku ne studiojme rrjete te nderlikuara. Jemi njohur disa vjet me pare kur zbuluam se na eshte dhene nga nje fjalim TED i shkurter mbi ekologjine e luftes, dhe zbuluam se na bashkonin idete qe ndanim para se te njiheshim. Me pas menduam, se mund te kete me mijera fjalime te tjera atje, mbi te gjitha fjalime te TEDx, qe po shfaqen ne te gjithe boten. Si jane te lidhura ato , dhe si ngjason biseda globale? Sean do ju tregoje pak se si e beme ate.
Sean Gourley: Exactly. So we took 24,000 TEDx Talks from around the world, 147 different countries, and we took these talks and we wanted to find the mathematical structures that underly the ideas behind them. And we wanted to do that so we could see how they connected with each other.
Sean Gourley: Pikerisht. Ne morem 24.000 fjalime TEDx nga e gjithe bota, 147 shtete te ndryshme, ajo cka donim te gjenim ne keto fjalime ishte strukturat matematikore qe fshehin idete pas tyre. Dhe donin ta benim kete ne menyre qe te shihnim se si lidheshin ato mes tyre.
And so, of course, if you're going to do this kind of stuff, you need a lot of data. So the data that you've got is a great thing called YouTube, and we can go down and basically pull all the open information from YouTube, all the comments, all the views, who's watching it, where are they watching it, what are they saying in the comments. But we can also pull up, using speech-to-text translation, we can pull the entire transcript, and that works even for people with kind of funny accents like myself. So we can take their transcript and actually do some pretty cool things. We can take natural language processing algorithms to kind of read through with a computer, line by line, extracting key concepts from this. And we take those key concepts and they sort of form this mathematical structure of an idea. And we call that the meme-ome. And the meme-ome, you know, quite simply, is the mathematics that underlies an idea, and we can do some pretty interesting analysis with it, which I want to share with you now.
Dhe sigurisht, nese do te besh dicka te tille, te duhen shume te dhena. Dhe te dhenat qe ti ke eshte nje dicka e madhe qe quhet YouTube, ku mund te nxjerrim te gjithe informacionin e hapur nga YouTube, te gjitha komentet, shikimet, kush po e sheh ate, ku po e shohin dhe cfare po thone ne komente. Por mund edhe te nxjerrim, duke perdorur perkthimet nga te folurit ne tekste, mund te perdorim te gjithe kopjen e shkruar, dhe kjo funksionon dhe per njerezit me dialekt pak qesharak si ky i imi. Pra ne mund te marim kopjen e shkruar dhe realisht te bejme disa gjera shume interesante. Mund te marim algoritme natyrore te perpunimit te gjuhes per te lexuar me nje kompjuter, rrjesht pas rrjeshti, duke nxjerre koncepte kyce nga kjo. I marim keto koncepte kyce qe perbejne strukturen matematikore te nje ideje. Dhe kete e quajme meme-ome. Meme-ome, shume thjesht eshte matematika ne bazen e nje ideje, dhe mund te bejme nje analize shume interesante me te, te cilen dua ta ndaj me ju.
So each idea has its own meme-ome, and each idea is unique with that, but of course, ideas, they borrow from each other, they kind of steal sometimes, and they certainly build on each other, and we can go through mathematically and take the meme-ome from one talk and compare it to the meme-ome from every other talk, and if there's a similarity between the two of them, we can create a link and represent that as a graph, just like Eric and I are connected.
Pra cdo ide ka meme-ome e vet, dhe cdo ide eshte unike, por sigurisht, idete, huazojne nga njera tjetra, madje dhe vjedhin nga njera-tjetra ndonjehere, dhe sigurisht ndertohen mbi njera tjetren keshtu mund te vazhdojme matematikisht dhe te marim meme-ome nga nje fjalim dhe ta krahasojme ate me meme-ome me cdo fjalim tjeter, dhe nese ka ngjashmeri mes dy nga ato, mund te krijojme nje lidhje si grafik, ashtu sic jam i lidhur une me Eric.
So that's theory, that's great. Let's see how it works in actual practice. So what we've got here now is the global footprint of all the TEDx Talks over the last four years exploding out around the world from New York all the way down to little old New Zealand in the corner. And what we did on this is we analyzed the top 25 percent of these, and we started to see where the connections occurred, where they connected with each other. Cameron Russell talking about image and beauty connected over into Europe. We've got a bigger conversation about Israel and Palestine radiating outwards from the Middle East. And we've got something a little broader like big data with a truly global footprint reminiscent of a conversation that is happening everywhere.
Pra kjo eshte teori. Kjo eshte e mrekullueshme. Le te shohim si funksionon ne praktike. Ajo cka kemi ketu eshte gjurma globale nga te gjitha fjalimet e TEDx per kater vitet e fundit qe shperthejne ne bote nga New York deri ne Zelanden e Re ketu ne qoshe. Ajo cka beme ketu ishte analiza e 25 perqind te ketyre, dhe filluam te shikonim se ku shfaqeshin lidhjet, atje ku bashkoheshin me njera tjetren. Cameron Russell duke folur mbi imazhin dhe bukurine lidhet me te gjithe Europen. Kemi nje diskutim me te madh mbi Israelin dhe Palestinen e cila perhapet drejt Lindjes se Mesme. Dhe kemi dicka me te gjere si te dhena te medha me gjurme te verteta globale e cila ngjason me nje bisede qe po ndodh kudo.
So from this, we kind of run up against the limits of what we can actually do with a geographic projection, but luckily, computer technology allows us to go out into multidimensional space. So we can take in our network projection and apply a physics engine to this, and the similar talks kind of smash together, and the different ones fly apart, and what we're left with is something quite beautiful.
Nga kjo, u gjendem disi kundrejt limiteve nga cka mund te bejme realisht me projektimin gjeografik, por fatmiresisht, teknologjia kompjuterike na lejon te dalim ne nje hapesire shume dimensionale. Keshtu mund te marim projektin tone te rrjetit dhe te aplikojme nje motor fizike ne kete, keshtu fjalimet e ngjashme pak a shume perplasen me njera tjetren, kurse ato te ndryshmet vecohen, dhe ajo cka na mbetet eshte dicka shume e bukur.
EB: So I want to just point out here that every node is a talk, they're linked if they share similar ideas, and that comes from a machine reading of entire talk transcripts, and then all these topics that pop out, they're not from tags and keywords. They come from the network structure of interconnected ideas. Keep going.
EB: Dua te nenvizoj ketu se cdo nyje eshte nje fjalim, ato lidhen nese ndajne te njejtat ide, dhe kjo del nga nje mekanizem lexues i kopjes se shkruar ne teresi, dhe me pas te gjitha subjektet qe ndahen, nuk jane nga etiketimet ose fjalet kyce. Ato vine nga struktura e rrjetit te ideve te nderlidhura. Vazhdo.
SG: Absolutely. So I got a little quick on that, but he's going to slow me down. We've got education connected to storytelling triangulated next to social media. You've got, of course, the human brain right next to healthcare, which you might expect, but also you've got video games, which is sort of adjacent, as those two spaces interface with each other.
SG. Absolutisht. U nxitova pak aty, por ai do me ngadalsoje pak. Kemi edukimin qe lidhet me tregimet ne trekendesh me median sociale. Keni sigurisht, trurin e njeriut prane kujdesit shendetesor, ku mund ta prisni, por gjithashtu keni dhe lojrat elektronike e cila eshte afer, ndersa keto dy hapesira interferojne me njera tjetren.
But I want to take you into one cluster that's particularly important to me, and that's the environment. And I want to kind of zoom in on that and see if we can get a little more resolution. So as we go in here, what we start to see, apply the physics engine again, we see what's one conversation is actually composed of many smaller ones. The structure starts to emerge where we see a kind of fractal behavior of the words and the language that we use to describe the things that are important to us all around this world. So you've got food economy and local food at the top, you've got greenhouse gases, solar and nuclear waste. What you're getting is a range of smaller conversations, each connected to each other through the ideas and the language they share, creating a broader concept of the environment. And of course, from here, we can go and zoom in and see, well, what are young people looking at? And they're looking at energy technology and nuclear fusion. This is their kind of resonance for the conversation around the environment. If we split along gender lines, we can see females resonating heavily with food economy, but also out there in hope and optimism.
Por dua tju terheq ne nje grumbull qe eshte ne vecanti shume i rendesishem per mua, dhe ky eshte mjedisi. Dhe dua ta zmadhoj pak ketu dhe te shohim nese mund te marim nje rezolucion pak me te larte. Pra duke u futur ketu, ajo cka fillojme te shohim, duke aplikuar perseri motorin e fizikes, shohim se nje bisede aktualisht eshte e perbere nga disa me te vogla. Struktura fillon te shfaqet ku shohim nje sjellje disi fraktale e fjaleve dhe gjuhes qe perdorim per te pershkruar gjera qe jane interesante per ne ne kete bote. Kemi ekonomine e ushqimit dhe ushqimin lokal ne skaj, kemi gazrat e serrave, mbetjet diellore dhe berthamore. Ajo cka merrni eshte nje linje bisedash me te vogla, te lidhura me njera tjetren ndermjet ideve dhe gjuhes qe ato ndajne, duke krijuar nje koncept me te gjere mbi mjedisin. Dhe sigurisht nga ketu, mund te shkojme dhe te zmadhojme e shohim, se cfare shohin te rinjte? Ata shohin teknologjine energjitike dhe fusionin berthamor. Kjo eshte rezonanca e tyre per bisedat mbi mjedisin. Nese do ndajme linjat gjinore, mund te shohim se gjinia femerore anon me shume ne ekonomine ushqimore, por gjithashtu ne shprese dhe optimizem.
And so there's a lot of exciting stuff we can do here, and I'll throw to Eric for the next part.
Dhe keshtu kemi disa gjera shume interesante qe mund te bejme ketu, dhe do tja kaloj Eric per pjesen tjeter.
EB: Yeah, I mean, just to point out here, you cannot get this kind of perspective from a simple tag search on YouTube. Let's now zoom back out to the entire global conversation out of environment, and look at all the talks together. Now often, when we're faced with this amount of content, we do a couple of things to simplify it. We might just say, well, what are the most popular talks out there? And a few rise to the surface. There's a talk about gratitude. There's another one about personal health and nutrition. And of course, there's got to be one about porn, right? And so then we might say, well, gratitude, that was last year. What's trending now? What's the popular talk now? And we can see that the new, emerging, top trending topic is about digital privacy.
EB: Po, dua te them thjesht per te theksuar nuk mund ta maresh kete perspektive nga nje etiketim i thjeshte ne YouTube. Tani le te zmadhojme te gjitha bisedat globale nga mjedisi, dhe te shohim gjithe fjalimet bashke. Shpesh ne hasim kete sasi permbajtjeje, dhe kryejme disa gjera per ti thjeshtuar. Edhe mund te themi, ne rregull, cilat jane fjalimet me te njohura aty? Dhe disa dalin ne siperfaqe. Ekziston nje fjalim mbi mirenjohjen. Eshte dhe nje tjeter mbi shendetin personal dhe ushqimin. Dhe sigurisht duhet te kete dhe nje mbi pornografine apo jo? Dhe atehere mund te themi, mirenjohja ishte vitin e kaluar. Por cfare eshte ne qarkullim tani? Cili eshte fjalimi me i njohur tani? Dhe mund te shohim se subjekti me ne qarkullim eshte ai mbi privatesine dixhitale.
So this is great. It simplifies things. But there's so much creative content that's just buried at the bottom. And I hate that. How do we bubble stuff up to the surface that's maybe really creative and interesting? Well, we can go back to the network structure of ideas to do that. Remember, it's that network structure that is creating these emergent topics, and let's say we could take two of them, like cities and genetics, and say, well, are there any talks that creatively bridge these two really different disciplines. And that's -- Essentially, this kind of creative remix is one of the hallmarks of innovation. Well here's one by Jessica Green about the microbial ecology of buildings. It's literally defining a new field. And we could go back to those topics and say, well, what talks are central to those conversations? In the cities cluster, one of the most central was one by Mitch Joachim about ecological cities, and in the genetics cluster, we have a talk about synthetic biology by Craig Venter. These are talks that are linking many talks within their discipline. We could go the other direction and say, well, what are talks that are broadly synthesizing a lot of different kinds of fields. We used a measure of ecological diversity to get this. Like, a talk by Steven Pinker on the history of violence, very synthetic.
Pra kjo eshte e mrekullueshme. Kjo i thjeshton gjerat. Por ka kaq shume subjekte me krijuese te cilat jane te varrosura ne fund. Dhe une e urrej kete. Si mund te nxjerrim ne siperfaqe gjera te cilat mund te jene krijuese dhe interesante? Mund ti kthehemi struktures se rrjetit te ideve per ta bere. Mbani mend, eshte ajo strukture rrjeti e cila krijon subjektet ne zhvillim, dhe le te themi qe mund te marrim dy nga ato, si qytete dhe gjenetika dhe te themi, a ekzistojne fjalime qe krijimtarisht lidh keto dy disiplina vertet te ndryshme. Dhe kjo eshte --Ne thelb, ky lloj remiksi kreativ eshte nje nga shenjat dalluese te risis. Ketu kemi nje nga Jessica Green mbi ekologjine mikrobiale te ndertesave. Kjo percakton vertet nje fushe te re. Dhe mund ti kthehemi ketyre subjekteve duke thene cilat fjalime kryesojne ne keto biseda? Ne grumbullin e qyteteve, nje nga me kryesoret eshte njera nga Mitch Joachim mbi ekologjine e qyteteve, dhe ne grumbullin e gjenetikes, kemi nje fjalim mbi biologjine sintetike nga Craig Venter. Keto jane fjalime te cilat permbajne shume fjalime ne disiplinen e tyre. Mund te shkojme ne nje tjeter drejtim e te themi cilat jane fjalimet qe gjeresisht sintetizojne shume fusha te ndryshme. Ne perdorem nje mates mbi diversitetin ekologjik per ta marr kete. Si fjalimi i Steven Pinker mbi historine e dhunes, shume sintetike.
And then, of course, there are talks that are so unique they're kind of out in the stratosphere, in their own special place, and we call that the Colleen Flanagan index. And if you don't know Colleen, she's an artist, and I asked her, "Well, what's it like out there in the stratosphere of our idea space?" And apparently it smells like bacon. I wouldn't know. So we're using these network motifs to find talks that are unique, ones that are creatively synthesizing a lot of different fields, ones that are central to their topic, and ones that are really creatively bridging disparate fields. Okay? We never would have found those with our obsession with what's trending now. And all of this comes from the architecture of complexity, or the patterns of how things are connected.
Sigurisht keto jane fjalime shume te vecanta qe pak a shume jane jashte stratosferes ne vendin e tyre te vecante, dhe ne e quajme ate indeksi Colleen Flanagan. Ne rast se nuk e njihni Collen, ajo eshte nje artiste, dhe une e pyeta ate, "Si eshte te jesh aty jashte ne stratosferen e hapesires se ideve?" Dhe me sa duket kishte nje ere si proshute e tymosur. Nuk kisha si ta dija. Pra ne perdorim keto modele rrjeti per te gjetur fjalime te vecanta, ato te cilat jane te sintetizuara krijimtarisht nga shume fusha te ndryshme, ato te cilat kryesojne subjektin e tyre, dhe ato te cilat lidhin krijimtarisht fusha te pangjashme. Ne nuk mund ti gjenim ato kurre me manine se cfare eshte ne qarkullim tani. Dhe e gjitha kjo vjen nga arkitektura e kompleksitetit, ose te modeleve te se si gjerat jane te lidhura.
SG: So that's exactly right. We've got ourselves in a world that's massively complex, and we've been using algorithms to kind of filter it down so we can navigate through it. And those algorithms, whilst being kind of useful, are also very, very narrow, and we can do better than that, because we can realize that their complexity is not random. It has mathematical structure, and we can use that mathematical structure to go and explore things like the world of ideas to see what's being said, to see what's not being said, and to be a little bit more human and, hopefully, a little smarter.
SG: Kjo eshte ekzaktesisht e vertete. Jemi ne nje bote e cila eshte masivisht komplekse, dhe ne kemi perdorur algoritme per ta filtrurar ate ne menyre qe ne te mund te lundrojme ne te. Dhe keto algoritme ndersa jane shume te dobishme dhe te mira jane gjithashtu dhe shume te kufizuara, dhe ne mund te bejme me shume se aq, sepse mund te kuptojme qe kompleksiteti i tyre nuk eshte i rastesishem. Ka nje strukture matematikore, dhe mund ta perdorim ate strukture matematikore per te zbuluar gjera si boten e ideve per te pare se cfare po thuhet, dhe cfare nuk po thuhet, dhe per te qene pak me njerezor dhe me shprese, pak me te zgjuar.
Thank you.
Faleminderit.
(Applause)
(Duartrokitje)