TED名人演讲稿人际关系的潜在影响.doc

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 wifes 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 daughters husband, he also was sick from his wifes exhaustion. And I was driving home one day, and I get a phone call from the husbands friend, calling mebecause he was depressed about what was happening to his friend. So here I get this call from this random guy thats having an experience thats being influenced by people at some social distance.对于我来说，这个故事是15年前开始的。当时我是芝加哥大学安养院的医生，在芝加哥的南边地区照顾临终的病人和他们的亲属。我借此来观察疾病晚期病人和家属所经历的一切。而在我的实验室里，我当时正在研究“寡妇效应”，这是社会科学中非常古老的一个观点，可追述到150年前，当时被称为是“心碎之死”。举个例子来说，如果我去世的话，我妻子在我逝世之后一年的死亡率会加倍。我当时照料的病人中，有一位是死于痴呆症的女士。和夫妻的例子不同的是，当时照顾这位女士的是她的女儿。这个女儿因为照顾老母而筋疲力竭，而女儿的丈夫也因为妻子的疲劳而患上疾病。有一天我正开车回家，收到一通来自这个丈夫的朋友的电话，原因是他为他朋友所经历的一切感到忧郁。我就这样神奇地接到一个陌生人的电话，全因为他的经历受到了一些和他有一定“社会距离”的人的影响。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 were embedded in these social networks, and how they affect our lives. So, social networks are these intricate things of beauty, and theyre 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?我也因此突然意识到了两件很简单的事情。首先，“寡妇效应”不仅仅局限于丈夫和妻子之间。其二，它也不仅仅局限于两个人之间。我开始以全新的视角观察这个世界，将世界看成是成双成对联系在一起的人们。我随后又意识到这些人，如果俩俩相配，便会变成四人小组。事实上，这些人都身处在其他各种人际关系中婚姻、伴侣、友情、等等。事实上，这些关联是如此之广泛，我们所有人都身处在这个广博的网络中，与彼此相连。所以我开始以全新的角度看待这个世界，并沉迷其中。我为我们是如何陷入这些社会网络中而着迷，也为这些网络是如何影响我们的生活而着迷。这些社会网络是错综的艺术之作，它们是如此的精致、如此复杂、如此无所不在，使得我们不得不询问它们存在的意义是什么。我们为什么会身陷这些社会网络中?它们是如何成立的?是如何工作的?它们是如何影响我们的?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. Its 2,200 people in the year 2000. Every dot is a person. We make the dot size proportional to peoples 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 youre 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. Its not obvious exactly whats 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?而我据此的第一个研究课题，不是死亡，而是肥胖症。突然间，讨论肥胖症变成了一个热门话题。我与同事James Fowler开始研讨肥胖症是否真的是一种流行病，是否可以从一个人传染到另一个人身上，就如我之前讨论的那四个人一样。 这里看到的是我们的初步研究结果。 这是2000年接受研究的2200人。每个圆点代表着一个人。圆点的大小和人的身形成正比。所以大的圆点代表身形大的人。除此之外，如果你的体重指数超过30的话，如果你被诊断有肥胖症，我们便把圆点涂成黄色。如果你这么大略地看看这张图的话，你也许可以看到肥胖的人和非肥胖的人有聚集的症状。但是这个视觉复杂性还是很高的，很难确切地说清其中的关联。除此之外，很多问题也立即产生。到底有多少聚集?所产生的聚集是不是要比单纯的巧合下所产生的聚集要多?聚集的大小是怎样?可以触及到多远?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 friends friends are obese, your risk of obesity is 25 percent higher. And then the next line over says if your friends friends friend, someone you probably dont even know, is obese, your risk of obesity is 10 percent higher. And its only when you get to your friends friends friends friends that theres no longer a relationship between that persons body size and your own body size.所以我们用数学的办法研究了一下这些聚集的大小。在这里可以看到，纵轴上代表的是，如果一个人的社会联系人中有人患有肥胖症的话，那么这个人患有肥胖症的几率会增加多少;横轴上代表的是，这两个人之间的分离指数。在最左端，你看到那条紫色线。它显示如果你的朋友们有肥胖症，你肥胖的可能性就会高出45%。接下来的那条红色线显示的是，如果你的朋友的朋友有肥胖症，你患肥胖症的可能性就会高出25%。 下一条线显示如果你朋友的朋友的朋友你可能都不认识这个人患有肥胖症的话，你患肥胖症的可能性就会高出10%。一直追溯到你朋友的朋友的朋友的朋友的时候，这层关系才会消失，这个人的身形和你的身形才不再会有关联。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 whats 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，造成这种聚集的原因有哪些呢?至少有三种可能。第一种就是当我体重增加时，也导致了你的体重增加，类似磁场感应，由一个人传到另一个人。另一种可能，很显然，就是同类的聚合效应，物以类聚、人以群分。我之所以和你建立关系，正是因为我们俩身形相似。而最后一种可能，叫做混杂因素，因为它模糊我们找到真正原因的能力。这意味着我的增肥，并没有直接导致你体重增加，我也不是因为咱俩身形相似才和你建立关系，而是因为我们俩都接触到了相同的经历，比如说健康俱乐部，导致我们俩同时减肥。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, Lets 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, whats spreading from person to person is not a behavior, but rather a norm: An idea is spreading.而当我们进一步研究这些数据的时候，我们发现了支持这三种可能的证据，包括磁场感应。我们发现如果你的朋友患有肥胖症，你在同一时期，患肥胖症的可能性会增加57%。造成这一现象的机理可以有很多。一种可能是你的朋友对你说他们的行为传染了你，比如他们会说：“咱俩一起去吃点糕点，喝瓶啤酒吧。”致命的搭配，但你还是接受了这个搭配，你也开始和你朋友一样开始增肥。另一个潜在的可能性是当他们开始增肥的时候，你对合理身形的概念也随之发生了改变。在这种情况下，从一个人传到另一个人身上的不再是行为，而是准则。一个想法得以蔓延。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.一些新闻头条记者借机盗用我们的研究。我记得当时纽约时报的头条是“你越来越肥吗? 怪罪你的那些肥朋友吧。”我们觉得很有趣的是，欧洲的头条记者们对此有不同的理解，他们的头条是：“你的朋友增肥了吗?也许你要自责一下。”(笑声)我们觉得这是对美国的一种很有趣的评论，一种事不关己、高高挂起，明哲保身的现象。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, theres not a Patient Zero of the obesity epidemic - if we find that guy, there was a spread of obesity out from him - its a multicentric epidemic. Lots of people are doing things at the same time. And Im 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. Were going to put this into motion now, taking daily cuts through the network for about 30 years.在这里我要澄清一下，我们并不认为我们的研究支持对某一种身材的歧视。我们的下一个问题是：我们能否在视觉上直接看到这种传染现象?体重的增加真的是从一个人身上传到另一个人身上吗?这就变得很复杂了，因为我们要考虑到这个网络的结构、关系之间的建筑构造，是随时都在变的。更何况，肥胖症并不是只有单一中心的流行病，没有肥胖流行病的“零号病人”如果找到这个人，那么肥胖症就是从他那边传出来的。但相反，肥胖症的流行有多个中心，多个人都在同时做着同样的事情。我将向你们展示一段30秒钟的视频演示，是花了我和James五年的人生才做好的。同样的，每个圆点都是一个人。每条连线都代表着某种人际关系。我们现在就要让它动起来，在30年间对这个网络进行每天的切割。The dot sizes are going to grow, youre going to see a sea of yellow take over. Youre 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, youre 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 thats changing across time, it has a memory, it moves, things flow within it, it has a kind of consistency - people can die, but it doesnt die; it still persists - and it has a kind of resilience that allows it to persist across time.圆点变得越来越大，你将看到一整片黄色，也会看到人的出生与死亡，圆点将会出现、又消逝。人际关系成立又瓦解。婚姻与离异，友情与断交，非常复杂，在短短30年间很多事情在发生，包括了肥胖的流行。在结尾处，你们将会看到肥胖者和非肥胖者在这个网络中出现扎堆的现象。 通过这个演示，我看待事物的方式得以改变，因为这个网络，这个随时间而变换的网络，是有记忆的，它移动着，其中的事物随其所动，它拥有着一种持久性;其中的人也许死去，但这种网络却不会死去，它仍旧持续着。它有着一种坚韧性，允许它恒久不变。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 dont 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. Theres emotional contagion that takes place in human populations. And so this function of emotions suggests that, in addition to any other purpose they serve, theyre 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.所以我开始将这些社会网络所散发的信号看作是活着的事物，可以放到显微镜下来研究、分析、理解。我们用各种各样的技术来做到这一点。我们开始研究其他各种现象。我们查看了吸烟和喝酒行为，投票行为，离婚也是可以传染的，还有自闭症。最终，我们对情感产生了兴趣。当我们有情感的时候，我们会将它们呈现出来。我们为什么要展示我们的情感呢?内在地感受情感，比如快乐与愤怒，当然是有其好处，但我们不单单是感受它们，我们也展示它们。我们不仅仅展示它们，其他人也可以阅读它们。其他人不仅仅可以阅读它们，他们也可以复制它们。在人类群体中，就有着情感的传染。情感的这一功能就表示除了其他作用之外，情感也是一种原始的表达方式。事实上，如果我们想真正地了解人类的情感，就要以这种方式来思考它们。Now, were 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 youre 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 dont do that in New York City. (Laughter) And I said, Everywhere else in the world, thats normal human behavior. And so theres 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 theres 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.我们已经习惯了在简单、简短的时间内来考虑情感。打个比方来说，我最近在纽约市演讲，其中说到：“当你在地铁上，车厢对面的人向你微笑时，你会下意识地回报以微笑。”他们看着我，说到：“我们纽约人才不会做那种事情。”我说：“世界上其他地方的人都会做，是人之常理。” 所以我们有一种很本能的方式在短时间内把情感传递给彼此。事实上，情感的传染可以更广阔一些，比如在暴乱中，我们会加强愤怒的表情。我们想要问的问题是：情感的传递能否超越地铁车厢上相互微笑的一小部分人，而是以比暴乱更持久的方式，长时间地在更多人之间传播?也许我们平静的表面下都蕴藏着某种时刻激荡着我们的某种暴乱。也许有某种情感蜂拥在社会网络中溅起涟漪。也许事实上，情感是有一种共有的存在性，不单单是个人的存在性。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 theyre happy and blue if theyre 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. Theres 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 - Im 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.这是我们用来研究这一现象所做出的早期图象之一。同样是一个社会网络，不过这一次我们把快乐的人涂成了黄色，难过的人涂成了蓝色，介于两者之间的人涂成了绿色。如果你看看这幅图片，你立马就能看到快乐的人和不快乐的人扎堆出现，同样地是传递到三层分离关系。你的直觉也许会告诉你不快乐的人在这个网络中占据着一个不同的结构点。这个网络有个中心部分、有个边缘地带，而不快乐的人好像都集中在边缘地带。再打个比方，如果你把这些社区网络想象成是一大块人类的绸缎我与你相连，你和她相连，无止境地延伸这块绸缎就好像是美国老式的被子一样，上面是一块块的补丁，有快乐的补丁，也有不快乐的。而你快乐与否就决定于你是否身处一块快乐补丁上。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 dont 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.所以像情感这种如此基础的东西都能按此来工作，我们不得不猜想，也许社会网路的基本原因是写在我们的基因中的。因为人类的社会网络，每当构造起来的时候， 总是会和这个网络的图片很相似，但它们却从来不会是这个样子的?它们为什么不是这个样子的呢?为什么我们不组成一个个有规则的格子框架的社会网络呢?人类社会网络惊人的样貌、其无所不在的特性和它们显而易见的功能，让我们猜想社会网络是否是我们进化的产物，而我们又是否进化出具有某种特殊结构的社会网络。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 thats not the case with real networks. So, for example, here is a real network of college students at an elite northeastern university. And now Im 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. Thats very obvious, we all know that. But certain other aspects of social network structure are not so obvious.首先注意要想搞懂这一切，我们必须先把这个网络结构分解一下注意到每个人在这个网络中的结构点和其他人都是一样的。但在真实的网络中，却不是这个样子的。好比说，这是东北部一所顶尖大学内大学生之间的真实网络图。我这里着重挑选了几个圆点，如果你仔细看看这些圆点，把左上角的点B和最右边的点D做比较。B有四个朋友从他那里延伸出来，D则是有六个朋友。所以这两个人的朋友数量有所不同这是显而易见的，我们都知道。但社会网络结构中的其他方面就没有这么明显了。Compare node B in the upper left to node A in the lower left. Now, those people both have four friends, but As friends all know each other, and Bs friends do not. So the friend of a friend of As is, back again, a friend of As, whereas the friend of a friend of Bs is not a friend of Bs, 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, Ive got six friends. Thats my social experience. But now we, with a birds 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? Youd 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.把左上角的点B和左下角的点A做比较。他俩都有四个朋友，但是A的朋友们彼此相知，B的朋友们却不是。所以A的一个朋友的朋友，反过来还是A的朋友，而B的一个朋友的朋友倒不一定是B的朋友，而是在网络中的更远处。这就是网络中的可传递性。最后再来比较点C和点D，两者都有六个朋友，如果你问他们：“你的社交生活怎样?”他们会说：“我有六个朋友。这就是我的社交经历。”但我们来鸟瞰这个网络，我们就会发现他们的社交圈是完全不同的。接下来的这个问题就可以培养你这方面的直觉：如果一种致命的病毒在这个网络里得以