For me, this story begins about 15 years ago, when I was a hospice doctor at the University of Chicago. And I was taking care of people who were dying and their families in the South Side of Chicago. And I was observing what happened to people and their families over the course of their terminal illness. And in my lab, I was studying the widower effect, which is a very old idea in the social sciences, going back 150 years, known as "dying of a broken heart." So, when I die, my wife's risk of death can double, for instance, in the first year. And I had gone to take care of one particular patient, a woman who was dying of dementia. And in this case, unlike this couple, she was being cared for by her daughter. And the daughter was exhausted from caring for her mother. And the daughter's husband, he also was sick from his wife's exhaustion. And I was driving home one day, and I get a phone call from the husband's friend, calling me because he was depressed about what was happening to his friend. So here I get this call from this random guy that's having an experience that's being influenced by people at some social distance.

對于我來說，這個故事是15年前開始的。當時我是芝加哥大學安養院的醫生，在芝加哥的南邊地區照顧臨終的病人和他們的親屬。我借此來觀察疾病晚期病人和家屬所經歷的一切。而在我的實驗室里，我當時正在研究“寡婦效應”，這是社會科學中非常古老的一個觀點，可追述到150年前，當時被稱為是“心碎之死”。舉個例子來說，如果我去世的話，我妻子在我逝世之后一年的死亡率會加倍。我當時照料的病人中，有一位是死于癡呆癥的女士。和夫妻的例子不同的是，當時照顧這位女士的是她的女兒。這個女兒因為照顧老母而筋疲力竭，而女兒的丈夫也因為妻子的疲勞而患上疾病。有一天我正開車回家，收到一通來自這個丈夫的朋友的電話，原因是他為他朋友所經歷的一切感到憂郁。我就這樣神奇地接到一個陌生人的電話，全因為他的經歷受到了一些和他有一定“社會距離”的人的影響。

And so I suddenly realized two very simple things: First, the widowhood effect was not restricted to husbands and wives. And second, it was not restricted to pairs of people. And I started to see the world in a whole new way, like pairs of people connected to each other. And then I realized that these individuals would be connected into foursomes with other pairs of people nearby. And then, in fact, these people were embedded in other sorts of relationships: marriage and spousal and friendship and other sorts of ties. And that, in fact, these connections were vast and that we were all embedded in this broad set of connections with each other. So I started to see the world in a completely new way and I became obsessed with this. I became obsessed with how it might be that we're embedded in these social networks, and how they affect our lives. So, social networks are these intricate things of beauty, and they're so elaborate and so complex and so ubiquitous, in fact, that one has to ask what purpose they serve. Why are we embedded in social networks? I mean, how do they form? How do they operate? And how do they effect us?

我也因此突然意識到了兩件很簡單的事情。首先，“寡婦效應”不僅僅局限于丈夫和妻子之間。其二，它也不僅僅局限于兩個人之間。我開始以全新的視角觀察這個世界，將世界看成是成雙成對聯系在一起的人們。我隨后又意識到這些人，如果倆倆相配，便會變成四人小組。事實上，這些人都身處在其他各種人際關系中──婚姻、伴侶、友情、等等。事實上，這些關聯是如此之廣泛，我們所有人都身處在這個廣博的網絡中，與彼此相連。所以我開始以全新的角度看待這個世界，并沉迷其中。我為我們是如何陷入這些社會網絡中而著迷，也為這些網絡是如何影響我們的生活而著迷。這些社會網絡是錯綜的藝術之作，它們是如此的精致、如此復雜、如此無所不在，使得我們不得不詢問它們存在的意義是什么。我們為什么會身陷這些社會網絡中？它們是如何成立的？是如何工作的？它們是如何影響我們的？

So my first topic with respect to this, was not death, but obesity. It had become trendy to speak about the "obesity epidemic." And, along with my collaborator, James Fowler, we began to wonder whether obesity really was epidemic and could it spread from person to person like the four people I discussed earlier. So this is a slide of some of our initial results. It's 2,200 people in the year 2000. Every dot is a person. We make the dot size proportional to people's body size; so bigger dots are bigger people. In addition, if your body size, if your BMI, your body mass index, is above 30 -- if you're clinically obese -- we also colored the dots yellow. So, if you look at this image, right away you might be able to see that there are clusters of obese and non-obese people in the image. But the visual complexity is still very high. It's not obvious exactly what's going on. In addition, some questions are immediately raised: How much clustering is there? Is there more clustering than would be due to chance alone? How big are the clusters? How far do they reach? And, most importantly, what causes the clusters?

而我據此的第一個研究課題，不是死亡，而是肥胖癥。突然間，討論肥胖癥變成了一個熱門話題。我與同事James Fowler開始研討肥胖癥是否真的是一種流行病，是否可以從一個人傳染到另一個人身上，就如我之前討論的那四個人一樣。 這里看到的是我們的初步研究結果。 這是2000年接受研究的2200人。每個圓點代表著一個人。圓點的大小和人的身形成正比。所以大的圓點代表身形大的人。除此之外，如果你的體重指數超過30的話，如果你被診斷有肥胖癥，我們便把圓點涂成黃色。如果你這么大略地看看這張圖的話，你也許可以看到肥胖的人和非肥胖的人有聚集的癥狀。但是這個視覺復雜性還是很高的，很難確切地說清其中的關聯。除此之外，很多問題也立即產生。到底有多少聚集？所產生的聚集是不是要比單純的巧合下所產生的聚集要多？聚集的大小是怎樣？可以觸及到多遠？最重要的是，聚集的原因是什么？

So we did some mathematics to study the size of these clusters. This here shows, on the Y-axis, the increase in the probability that a person is obese given that a social contact of theirs is obese and, on the X-axis, the degrees of separation between the two people. On the far left, you see the purple line. It says that, if your friends are obese, your risk of obesity is 45 percent higher. And the next bar over, the [red] line, says if your friend's friends are obese, your risk of obesity is 25 percent higher. And then the next line over says if your friend's friend's friend, someone you probably don't even know, is obese, your risk of obesity is 10 percent higher. And it's only when you get to your friend's friend's friend's friends that there's no longer a relationship between that person's body size and your own body size.

所以我們用數學的辦法研究了一下這些聚集的大小。在這里可以看到，縱軸上代表的是，如果一個人的社會聯系人中有人患有肥胖癥的話，那么這個人患有肥胖癥的幾率會增加多少；橫軸上代表的是，這兩個人之間的分離指數。在最左端，你看到那條紫色線。它顯示如果你的朋友們有肥胖癥，你肥胖的可能性就會高出45%。接下來的那條紅色線顯示的是，如果你的朋友的朋友有肥胖癥，你患肥胖癥的可能性就會高出25%。 下一條線顯示如果你朋友的朋友的朋友──你可能都不認識這個人──患有肥胖癥的話，你患肥胖癥的可能性就會高出10%。一直追溯到你朋友的朋友的朋友的朋友的時候，這層關系才會消失，這個人的身形和你的身形才不再會有關聯。

Well, what might be causing this clustering? There are at least three possibilities: One possibility is that, as I gain weight, it causes you to gain weight. A kind of induction, a kind of spread from person to person. Another possibility, very obvious, is homophily, or, birds of a feather flock together; here, I form my tie to you because you and I share a similar body size. And the last possibility is what is known as confounding, because it confounds our ability to figure out what's going on. And here, the idea is not that my weight gain is causing your weight gain, nor that I preferentially form a tie with you because you and I share the same body size, but rather that we share a common exposure to something, like a health club that makes us both lose weight at the same time.

所以，造成這種聚集的原因有哪些呢？至少有三種可能。第一種就是當我體重增加時，也導致了你的體重增加，類似磁場感應，由一個人傳到另一個人。另一種可能，很顯然，就是同類的聚合效應，物以類聚、人以群分。我之所以和你建立關系，正是因為我們倆身形相似。而最后一種可能，叫做混雜因素，因為它模糊我們找到真正原因的能力。這意味著我的增肥，并沒有直接導致你體重增加，我也不是因為咱倆身形相似才和你建立關系，而是因為我們倆都接觸到了相同的經歷，比如說健康俱樂部，導致我們倆同時減肥。

When we studied these data, we found evidence for all of these things, including for induction. And we found that if your friend becomes obese, it increases your risk of obesity by about 57 percent in the same given time period. There can be many mechanisms for this effect: One possibility is that your friends say to you something like -- you know, they adopt a behavior that spreads to you -- like, they say, "Let's go have muffins and beer," which is a terrible combination. (Laughter) But you adopt that combination, and then you start gaining weight like them. Another more subtle possibility is that they start gaining weight, and it changes your ideas of what an acceptable body size is. Here, what's spreading from person to person is not a behavior, but rather a norm: An idea is spreading.

而當我們進一步研究這些數據的時候，我們發現了支持這三種可能的證據，包括磁場感應。我們發現如果你的朋友患有肥胖癥，你在同一時期，患肥胖癥的可能性會增加57%。造成這一現象的機理可以有很多。一種可能是你的朋友對你說──他們的行為傳染了你，比如他們會說：“咱倆一起去吃點糕點，喝瓶啤酒吧。”致命的搭配，但你還是接受了這個搭配，你也開始和你朋友一樣開始增肥。另一個潛在的可能性是當他們開始增肥的時候，你對合理身形的概念也隨之發生了改變。在這種情況下，從一個人傳到另一個人身上的不再是行為，而是準則。一個想法得以蔓延。

Now, headline writers had a field day with our studies. I think the headline in The New York Times was, "Are you packing it on? Blame your fat friends." (Laughter) What was interesting to us is that the European headline writers had a different take: They said, "Are your friends gaining weight? Perhaps you are to blame." (Laughter) And we thought this was a very interesting comment on America, and a kind of self-serving, "not my responsibility" kind of phenomenon.

一些新聞頭條記者借機盜用我們的研究。我記得當時《紐約時報》的頭條是“你越來越肥嗎？ 怪罪你的那些肥朋友吧。”我們覺得很有趣的是，歐洲的頭條記者們對此有不同的理解，他們的頭條是：“你的朋友增肥了嗎？也許你要自責一下。”（笑聲）我們覺得這是對美國的一種很有趣的評論，一種事不關己、高高掛起，明哲保身的現象。

Now, I want to be very clear: We do not think our work should or could justify prejudice against people of one or another body size at all. Our next questions was: Could we actually visualize this spread? Was weight gain in one person actually spreading to weight gain in another person? And this was complicated because we needed to take into account the fact that the network structure, the architecture of the ties, was changing across time. In addition, because obesity is not a unicentric epidemic, there's not a Patient Zero of the obesity epidemic -- if we find that guy, there was a spread of obesity out from him -- it's a multicentric epidemic. Lots of people are doing things at the same time. And I'm about to show you a 30 second video animation that took me and James five years of our lives to do. So, again, every dot is a person. Every tie between them is a relationship. We're going to put this into motion now, taking daily cuts through the network for about 30 years.

在這里我要澄清一下，我們并不認為我們的研究支持對某一種身材的歧視。我們的下一個問題是：我們能否在視覺上直接看到這種傳染現象？體重的增加真的是從一個人身上傳到另一個人身上嗎？這就變得很復雜了，因為我們要考慮到這個網絡的結構、關系之間的建筑構造，是隨時都在變的。更何況，肥胖癥并不是只有單一中心的流行病，沒有肥胖流行病的“零號病人”──如果找到這個人，那么肥胖癥就是從他那邊傳出來的。但相反，肥胖癥的流行有多個中心，多個人都在同時做著同樣的事情。我將向你們展示一段30秒鐘的視頻演示，是花了我和James五年的人生才做好的。同樣的，每個圓點都是一個人。每條連線都代表著某種人際關系。我們現在就要讓它動起來，在30年間對這個網絡進行每天的切割。

The dot sizes are going to grow, you're going to see a sea of yellow take over. You're going to see people be born and die -- dots will appear and disappear -- ties will form and break, marriages and divorces, friendings and defriendings. A lot of complexity, a lot is happening just in this 30-year period that includes the obesity epidemic. And, by the end, you're going to see clusters of obese and non-obese individuals within the network. Now, when looked at this, it changed the way I see things, because this thing, this network that's changing across time, it has a memory, it moves, things flow within it, it has a kind of consistency -- people can die, but it doesn't die; it still persists -- and it has a kind of resilience that allows it to persist across time.

圓點變得越來越大，你將看到一整片黃色，也會看到人的出生與死亡，圓點將會出現、又消逝。人際關系成立又瓦解。婚姻與離異，友情與斷交，非常復雜，在短短30年間很多事情在發生，包括了肥胖的流行。在結尾處，你們將會看到肥胖者和非肥胖者在這個網絡中出現扎堆的現象。 通過這個演示，我看待事物的方式得以改變，因為這個網絡，這個隨時間而變換的網絡，是有記憶的，它移動著，其中的事物隨其所動，它擁有著一種持久性；其中的人也許死去，但這種網絡卻不會死去，它仍舊持續著。它有著一種堅韌性，允許它恒久不變。

And so, I came to see these kinds of social networks as living things, as living things that we could put under a kind of microscope to study and analyze and understand. And we used a variety of techniques to do this. And we started exploring all kinds of other phenomena. We looked at smoking and drinking behavior, and voting behavior, and divorce -- which can spread -- and altruism. And, eventually, we became interested in emotions. Now, when we have emotions, we show them. Why do we show our emotions? I mean, there would be an advantage to experiencing our emotions inside, you know, anger or happiness. But we don't just experience them, we show them. And not only do we show them, but others can read them. And, not only can they read them, but they copy them. There's emotional contagion that takes place in human populations. And so this function of emotions suggests that, in addition to any other purpose they serve, they're a kind of primitive form of communication. And that, in fact, if we really want to understand human emotions, we need to think about them in this way.

所以我開始將這些社會網絡所散發的信號看作是活著的事物，可以放到顯微鏡下來研究、分析、理解。我們用各種各樣的技術來做到這一點。我們開始研究其他各種現象。我們查看了吸煙和喝酒行為，投票行為，離婚─—也是可以傳染的，還有自閉癥。最終，我們對情感產生了興趣。當我們有情感的時候，我們會將它們呈現出來。我們為什么要展示我們的情感呢？內在地感受情感，比如快樂與憤怒，當然是有其好處，但我們不單單是感受它們，我們也展示它們。我們不僅僅展示它們，其他人也可以閱讀它們。其他人不僅僅可以閱讀它們，他們也可以復制它們。在人類群體中，就有著情感的傳染。情感的這一功能就表示除了其他作用之外，情感也是一種原始的表達方式。事實上，如果我們想真正地了解人類的情感，就要以這種方式來思考它們。

Now, we're accustomed to thinking about emotions in this way, in simple, sort of, brief periods of time. So, for example, I was giving this talk recently in New York City, and I said, "You know when you're on the subway and the other person across the subway car smiles at you, and you just instinctively smile back?" And they looked at me and said, "We don't do that in New York City." (Laughter) And I said, "Everywhere else in the world, that's normal human behavior." And so there's a very instinctive way in which we briefly transmit emotions to each other. And, in fact, emotional contagion can be broader still. Like we could have punctuated expressions of anger, as in riots. The question that we wanted to ask was: Could emotion spread, in a more sustained way than riots, across time and involve large numbers of people, not just this pair of individuals smiling at each other in the subway car? Maybe there's a kind of below the surface, quiet riot that animates us all the time. Maybe there are emotional stampedes that ripple through social networks. Maybe, in fact, emotions have a collective existence, not just an individual existence.

我們已經習慣了在簡單、簡短的時間內來考慮情感。打個比方來說，我最近在紐約市演講，其中說到：“當你在地鐵上，車廂對面的人向你微笑時，你會下意識地回報以微笑。”他們看著我，說到：“我們紐約人才不會做那種事情。”我說：“世界上其他地方的人都會做，是人之常理。” 所以我們有一種很本能的方式在短時間內把情感傳遞給彼此。事實上，情感的傳染可以更廣闊一些，比如在暴亂中，我們會加強憤怒的表情。我們想要問的問題是：情感的傳遞能否超越地鐵車廂上相互微笑的一小部分人，而是以比暴亂更持久的方式，長時間地在更多人之間傳播？也許我們平靜的表面下都蘊藏著某種時刻激蕩著我們的某種暴亂。也許有某種情感蜂擁在社會網絡中濺起漣漪。也許事實上，情感是有一種共有的存在性，不單單是個人的存在性。

And this is one of the first images we made to study this phenomenon. Again, a social network, but now we color the people yellow if they're happy and blue if they're sad and green in between. And if you look at this image, you can right away see clusters of happy and unhappy people, again, spreading to three degrees of separation. And you might form the intuition that the unhappy people occupy a different structural location within the network. There's a middle and an edge to this network, and the unhappy people seem to be located at the edges. So to invoke another metaphor, if you imagine social networks as a kind of vast fabric of humanity -- I'm connected to you and you to her, on out endlessly into the distance -- this fabric is actually like an old-fashioned American quilt, and it has patches on it: happy and unhappy patches. And whether you become happy or not depends in part on whether you occupy a happy patch.

這是我們用來研究這一現象所做出的早期圖象之一。同樣是一個社會網絡，不過這一次我們把快樂的人涂成了黃色，難過的人涂成了藍色，介于兩者之間的人涂成了綠色。如果你看看這幅圖片，你立馬就能看到快樂的人和不快樂的人扎堆出現，同樣地是傳遞到三層分離關系。你的直覺也許會告訴你不快樂的人在這個網絡中占據著一個不同的結構點。這個網絡有個中心部分、有個邊緣地帶，而不快樂的人好像都集中在邊緣地帶。再打個比方，如果你把這些社區網絡想象成是一大塊人類的綢緞──我與你相連，你和她相連，無止境地延伸──這塊綢緞就好像是美國老式的被子一樣，上面是一塊塊的補丁，有快樂的補丁，也有不快樂的。而你快樂與否就決定于你是否身處一塊快樂補丁上。

So, this work with emotions, which are so fundamental, then got us to thinking about: Maybe the fundamental causes of human social networks are somehow encoded in our genes. Because human social networks, whenever they are mapped, always kind of look like this: the picture of the network. But they never look like this. Why do they not look like this? Why don't we form human social networks that look like a regular lattice? Well, the striking patterns of human social networks, their ubiquity and their apparent purpose beg questions about whether we evolved to have human social networks in the first place, and whether we evolved to form networks with a particular structure.

所以像情感這種如此基礎的東西都能按此來工作，我們不得不猜想，也許社會網路的基本原因是寫在我們的基因中的。因為人類的社會網絡，每當構造起來的時候， 總是會和這個網絡的圖片很相似，但它們卻從來不會是這個樣子的？它們為什么不是這個樣子的呢？為什么我們不組成一個個有規則的格子框架的社會網絡呢？人類社會網絡驚人的樣貌、其無所不在的特性和它們顯而易見的功能，讓我們猜想社會網絡是否是我們進化的產物，而我們又是否進化出具有某種特殊結構的社會網絡。

And notice first of all -- so, to understand this, though, we need to dissect network structure a little bit first -- and notice that every person in this network has exactly the same structural location as every other person. But that's not the case with real networks. So, for example, here is a real network of college students at an elite northeastern university. And now I'm highlighting a few dots. If you look here at the dots, compare node B in the upper left to node D in the far right; B has four friends coming out from him and D has six friends coming out from him. And so, those two individuals have different numbers of friends. That's very obvious, we all know that. But certain other aspects of social network structure are not so obvious.

首先注意——要想搞懂這一切，我們必須先把這個網絡結構分解一下——注意到每個人在這個網絡中的結構點和其他人都是一樣的。但在真實的網絡中，卻不是這個樣子的。好比說，這是東北部一所頂尖大學內大學生之間的真實網絡圖。我這里著重挑選了幾個圓點，如果你仔細看看這些圓點，把左上角的點B和最右邊的點D做比較。B有四個朋友從他那里延伸出來，D則是有六個朋友。所以這兩個人的朋友數量有所不同──這是顯而易見的，我們都知道。但社會網絡結構中的其他方面就沒有這么明顯了。

Compare node B in the upper left to node A in the lower left. Now, those people both have four friends, but A's friends all know each other, and B's friends do not. So the friend of a friend of A's is, back again, a friend of A's, whereas the friend of a friend of B's is not a friend of B's, but is farther away in the network. This is known as transitivity in networks. And, finally, compare nodes C and D: C and D both have six friends. If you talk to them, and you said, "What is your social life like?" they would say, "I've got six friends. That's my social experience." But now we, with a bird's eye view looking at this network, can see that they occupy very different social worlds. And I can cultivate that intuition in you by just asking you: Who would you rather be if a deadly germ was spreading through the network? Would you rather be C or D? You'd rather be D, on the edge of the network. And now who would you rather be if a juicy piece of gossip -- not about you -- was spreading through the network? (Laughter) Now, you would rather be C.

把左上角的點B和左下角的點A做比較。他倆都有四個朋友，但是A的朋友們彼此相知，B的朋友們卻不是。所以A的一個朋友的朋友，反過來還是A的朋友，而B的一個朋友的朋友倒不一定是B的朋友，而是在網絡中的更遠處。這就是網絡中的可傳遞性。最后再來比較點C和點D，兩者都有六個朋友，如果你問他們：“你的社交生活怎樣？”他們會說：“我有六個朋友。這就是我的社交經歷。”但我們來鳥瞰這個網絡，我們就會發現他們的社交圈是完全不同的。接下來的這個問題就可以培養你這方面的直覺：如果一種致命的病毒在這個網絡里得以擴散， 你希望你是其中的哪一位？你是想當C還是想當D？你當然是想當D，處在網絡的邊緣。如果一條跟你無關的八卦新聞在這個網絡里散播，你又會想當誰呢？這次你會想當C。

So different structural locations have different implications for your life. And, in fact, when we did some experiments looking at this, what we found is that 46 percent of the variation in how many friends you have is explained by your genes. And this is not surprising. We know that some people are born shy and some are born gregarious. That's obvious. But we also found some non-obvious things. For instance, 47 percent in the variation in whether your friends know each other is attributable to your genes. Whether your friends know each other has not just to do with their genes, but with yours. And we think the reason for this is that some people like to introduce their friends to each other -- you know who you are -- and others of you keep them apart and don't introduce your friends to each other. And so some people knit together the networks around them, creating a kind of dense web of ties in which they're comfortably embedded. And finally, we even found that 30 percent of the variation in whether or not people are in the middle or on the edge of the network can also be attributed to their genes. So whether you find yourself in the middle or on the edge is also partially heritable.

所以不同的結構點對你的人生有著不同的影響。事實上，我們的實驗結果表明，朋友數量的差異有46%都是可以通過基因得以解釋。這并不奇怪。因為我們知道，有的人生來靦腆，有的人生來合群。這是顯而易見的。但我們也發現了一些不是那么明顯的東西。比如，你的朋友們是否認識彼此，其中47%的差異都是和你的基因有關。你的朋友們是否認識彼此不僅僅和他們自己的基因有關，也和你的基因有關。我們認為其中的原因就在于有的人喜歡把自己的朋友介紹給彼此──沒錯，說的就是你──而其他人喜歡把朋友們分開，不喜歡介紹給彼此。所以有些人將他們身邊的網絡們編織在一起，構成了緊密相聯的深層網絡，而他們則是舒服地身處其中。最后，我們甚至發現人們是身處網絡中心還是邊緣，30%的差異也是和他們的基因相關。所以你是在中心還是邊緣，有一部分是遺傳的。

Now, what is the point of this? How does this help us understand? How does this help us figure out some of the problems that are affecting us these days? Well, the argument I'd like to make is that networks have value. They are a kind of social capital. New properties emerge because of our embeddedness in social networks, and these properties inhere in the structure of the networks, not just in the individuals within them. So think about these two common objects. They're both made of carbon, and yet one of them has carbon atoms in it that are arranged in one particular way -- on the left -- and you get graphite, which is soft and dark. But if you take the same carbon atoms and interconnect them a different way, you get diamond, which is clear and hard. And those properties of softness and hardness and darkness and clearness do not reside in the carbon atoms; they reside in the interconnections between the carbon atoms, or at least arise because of the interconnections between the carbon atoms. So, similarly, the pattern of connections among people confers upon the groups of people different properties. It is the ties between people that makes the whole greater than the sum of its parts. And so it is not just what's happening to these people -- whether they're losing weight or gaining weight, or becoming rich or becoming poor, or becoming happy or not becoming happy -- that affects us; it's also the actual architecture of the ties around us.

說這些的目的是什么呢？如何加深我們的理解？如何幫助我們解決現今與我們生活息息相關的各種問題呢？我的論點是這些社會網絡充滿價值。 他們好比一種社交資產。 由于我們身陷其中，新的網絡屬性會出現，而這些屬性是繼承在網絡的結構之中，不僅僅是在網絡中的個人身上。 所以想想這兩個日常用品，他們都是由碳做成的，不過其中的一個是由碳原子以獨特的方式組合而成的，形成了左手邊的石墨，柔軟和漆黑。但如果你將相同的碳原子以不同的方式關聯到一起，就會得到鉆石，透徹而堅硬。而這些柔軟、堅硬、漆黑和透徹的屬性并不是存在于碳原子本身中。而是存在于碳原子之間的聯系中，或者至少是由于這些聯系造成的。同樣的，人與人之間的關聯形態也是賦予了各組群不同的屬性。正是人與人之間的關聯使得這個世界要比單單各部分的總和偉大許多。所以不僅僅是這些人所經歷的事情──他們在減肥還是在增肥，在變富還是在變窮，在快樂還是在不快樂──影響著我們； 同時影響我們的還有我們彼此關系所組成的實質結構。

Our experience of the world depends on the actual structure of the networks in which we're residing and on all the kinds of things that ripple and flow through the network. Now, the reason, I think, that this is the case is that human beings assemble themselves and form a kind of superorganism. Now, a superorganism is a collection of individuals which show or evince behaviors or phenomena that are not reducible to the study of individuals and that must be understood by reference to, and by studying, the collective. Like, for example, a hive of bees that's finding a new nesting site, or a flock of birds that's evading a predator, or a flock of birds that's able to pool its wisdom and navigate and find a tiny speck of an island in the middle of the Pacific, or a pack of wolves that's able to bring down larger prey. Superorganisms have properties that cannot be understood just by studying the individuals. I think understanding social networks and how they form and operate can help us understand not just health and emotions but all kinds of other phenomena -- like crime, and warfare, and economic phenomena like bank runs and market crashes and the adoption of innovation and the spread of product adoption.

我們在這個世界的經歷取決于我們所處網絡的實質結構，以及激蕩和流動于這個網絡中的各種事物。我認為，其原因就在于人類可以組織在一起組成一個“超級生物體”。這個“超級生物體”就好像是每個個體的集合，展示或標注某些無法在個體層面上研究的行為和現象，是只能通過對整體的探討和研究來獲得了解，就好比一窩尋找新的筑巢之地的蜜蜂；又好比是一個躲避捕食者的鳥群；或是可以集中智慧、辨清方向、找到太平洋之中飄蕩小島的鳥群；抑或是可以捕捉巨大獵物的狼群。超級生物體的特性是無法通過對個體的研究得以完全理解的。我認為通過對社會網絡的理解，研究它們是如何構成和運行的，能夠幫助我們了解不僅僅是健康和情感，還有許多其他的各種現象，比如犯罪和福利以及經濟現象比如銀行擠兌和市場崩盤，再有就是新技術的引用以及產品使用的擴展。

Now, look at this. I think we form social networks because the benefits of a connected life outweigh the costs. If I was always violent towards you or gave you misinformation or made you sad or infected you with deadly germs, you would cut the ties to me, and the network would disintegrate. So the spread of good and valuable things is required to sustain and nourish social networks. Similarly, social networks are required for the spread of good and valuable things, like love and kindness and happiness and altruism and ideas. I think, in fact, that if we realized how valuable social networks are, we'd spend a lot more time nourishing them and sustaining them, because I think social networks are fundamentally related to goodness. And what I think the world needs now is more connections.

看看這個。我認為我們組建社會網絡的原因是因為一個與人相連的生活模式要利大于弊。如果我總是對你很暴力給你錯誤的信息，或是使你難過，或是讓你染上致命的疾病，你就會和我斷交，這個網絡也就會瓦解。所以好的、有價值的事物的傳播是維持、滋潤社會網絡的必要條件。同樣的，社會網絡也是傳播這些好的、有價值的事物的必要條件，比如關愛與慈悲，快樂和博愛，以及想法。我認為，事實上，如果我們可以意識到社會網絡的價值所在，我們將會花費更多的時間來滋養、維持它們，因為我認為社會網絡在本質上是與美好相連的，而我認為我們這個世界上所需要的，正是更多的關聯。

Thank you.

謝謝大家。

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（來源：滬江網? 編輯：Julie）