我們都身處在由朋友、家人、同事等所構(gòu)建的龐大的社會(huì)網(wǎng)絡(luò)之中。醫(yī)學(xué)社會(huì)學(xué)家尼古拉斯追蹤發(fā)現(xiàn)了一系列的特質(zhì)，諸如快樂和肥胖，是如何傳遞的，解釋了你在社會(huì)網(wǎng)絡(luò)中所處的地位是如何以你意想不到的方式影響著你的生活。
    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.
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    對(duì)于我來說，這個(gè)故事是15年前開始的。當(dāng)時(shí)我是芝加哥大學(xué)安養(yǎng)院的醫(yī)生，在芝加哥的南邊地區(qū)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(jīng)歷的一切。而在我的實(shí)驗(yàn)室里，我當(dāng)時(shí)正在研究“寡婦效應(yīng)”，這是社會(huì)科學(xué)中非常古老的一個(gè)觀點(diǎn)，可追述到150年前，當(dāng)時(shí)被稱為是“心碎之死”。舉個(gè)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(huì)加倍。我當(dāng)時(shí)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(dāng)時(shí)照顧這位女士的是她的女兒。這個(gè)女兒因?yàn)檎疹櫪夏付钇Ａ?，而女兒的丈夫也因?yàn)槠拮拥钠诙忌霞膊?。有一天我正開車回家，收到一通來自這個(gè)丈夫的朋友的電話，原因是他為他朋友所經(jīng)歷的一切感到憂郁。我就這樣神奇地接到一個(gè)陌生人的電話，全因?yàn)樗慕?jīng)歷受到了一些和他有一定“社會(huì)距離”的人的影響。
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    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?
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    我也因此突然意識(shí)到了兩件很簡(jiǎn)單的事情。首先，“寡婦效應(yīng)”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(gè)人之間。我開始以全新的視角觀察這個(gè)世界，將世界看成是成雙成對(duì)聯(lián)系在一起的人們。我隨后又意識(shí)到這些人，如果倆倆相配，便會(huì)變成四人小組。事實(shí)上，這些人都身處在其他各種人際關(guān)系中──婚姻、伴侶、友情、等等。事實(shí)上，這些關(guān)聯(lián)是如此之廣泛，我們所有人都身處在這個(gè)廣博的網(wǎng)絡(luò)中，與彼此相連。所以我開始以全新的角度看待這個(gè)世界，并沉迷其中。我為我們是如何陷入這些社會(huì)網(wǎng)絡(luò)中而著迷，也為這些網(wǎng)絡(luò)是如何影響我們的生活而著迷。這些社會(huì)網(wǎng)絡(luò)是錯(cuò)綜的藝術(shù)之作，它們是如此的精致、如此復(fù)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?yōu)槭裁磿?huì)身陷這些社會(huì)網(wǎng)絡(luò)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?
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    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?
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    而我據(jù)此的第一個(gè)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(gè)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(gè)人傳染到另一個(gè)人身上，就如我之前討論的那四個(gè)人一樣。 這里看到的是我們的初步研究結(jié)果。 這是2000年接受研究的2200人。每個(gè)圓點(diǎn)代表著一個(gè)人。圓點(diǎn)的大小和人的身形成正比。所以大的圓點(diǎn)代表身形大的人。除此之外，如果你的體重指數(shù)超過30的話，如果你被診斷有肥胖癥，我們便把圓點(diǎn)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(gè)視覺復(fù)雜性還是很高的，很難確切地說清其中的關(guān)聯(lián)。除此之外，很多問題也立即產(chǎn)生。到底有多少聚集?所產(chǎn)生的聚集是不是要比單純的巧合下所產(chǎn)生的聚集要多?聚集的大小是怎樣?可以觸及到多遠(yuǎn)?最重要的是，聚集的原因是什么?
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    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(shù)學(xué)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(gè)人的社會(huì)聯(lián)系人中有人患有肥胖癥的話，那么這個(gè)人患有肥胖癥的幾率會(huì)增加多少;橫軸上代表的是，這兩個(gè)人之間的分離指數(shù)。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(huì)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(huì)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(rèn)識(shí)這個(gè)人──患有肥胖癥的話，你患肥胖癥的可能性就會(huì)高出10%。一直追溯到你朋友的朋友的朋友的朋友的時(shí)候，這層關(guān)系才會(huì)消失，這個(gè)人的身形和你的身形才不再會(huì)有關(guān)聯(lián)。
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    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(dāng)我體重增加時(shí)，也導(dǎo)致了你的體重增加，類似磁場(chǎng)感應(yīng)，由一個(gè)人傳到另一個(gè)人。另一種可能，很顯然，就是同類的聚合效應(yīng)，物以類聚、人以群分。我之所以和你建立關(guān)系，正是因?yàn)槲覀儌z身形相似。而最后一種可能，叫做混雜因素，因?yàn)樗：覀冋业秸嬲虻哪芰?。這意味著我的增肥，并沒有直接導(dǎo)致你體重增加，我也不是因?yàn)樵蹅z身形相似才和你建立關(guān)系，而是因?yàn)槲覀儌z都接觸到了相同的經(jīng)歷，比如說健康俱樂部，導(dǎo)致我們倆同時(shí)減肥。
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    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(dāng)我們進(jìn)一步研究這些數(shù)據(jù)的時(shí)候，我們發(fā)現(xiàn)了支持這三種可能的證據(jù)，包括磁場(chǎng)感應(yīng)。我們發(fā)現(xiàn)如果你的朋友患有肥胖癥，你在同一時(shí)期，患肥胖癥的可能性會(huì)增加57%。造成這一現(xiàn)象的機(jī)理可以有很多。一種可能是你的朋友對(duì)你說──他們的行為傳染了你，比如他們會(huì)說：“咱倆一起去吃點(diǎn)糕點(diǎn)，喝瓶啤酒吧?！敝旅拇钆洌氵€是接受了這個(gè)搭配，你也開始和你朋友一樣開始增肥。另一個(gè)潛在的可能性是當(dāng)他們開始增肥的時(shí)候，你對(duì)合理身形的概念也隨之發(fā)生了改變。在這種情況下，從一個(gè)人傳到另一個(gè)人身上的不再是行為，而是準(zhǔn)則。一個(gè)想法得以蔓延。
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    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?lì)^條記者借機(jī)盜用我們的研究。我記得當(dāng)時(shí)《紐約時(shí)報(bào)》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(duì)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(zé)一下。”(笑聲)我們覺得這是對(duì)美國的一種很有趣的評(píng)論，一種事不關(guān)己、高高掛起，明哲保身的現(xiàn)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.
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