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.
對於我來說，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。我藉此來觀察疾病晚期病人和家屬所經歷的一切。而在我的實驗室裡，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，我妻子在我逝世之後一年的死亡率會加倍。我當時照料的病人中，有一位是死於痴呆症的女士。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鬱。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」不僅僅局限於丈夫和妻子之間。其二，它也不僅僅局限於兩個人之間。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繫在一起的人們。我隨後又意識到這些人，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係中──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，並沉迷其中。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，它們是如此的精緻、如此複雜、如此無所不在，使得我們不得不詢問它們存在的意義是什麼。我們為什麼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，而是肥胖症。突然間，討論肥胖症變成了一個熱門話題。我與同事James Fowler開始研討肥胖症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。 這裡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症，我們便把圓點塗成黃色。如果你這麼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症狀。但是這個視覺複雜性還是很高的，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，聚集的原因是什麼?
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。在這裡可以看到，縱軸上代表的是，如果一個人的社會聯繫人中有人患有肥胖症的話，那麼這個人患有肥胖症的機率會增加多少;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症，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症，你患肥胖症的可能性就會高出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──患有肥胖症的話，你患肥胖症的可能性就會高出10%。一直追溯到你朋友的朋友的朋友的朋友的時候，這層關係才會消失，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係，正是因為我們倆身形相似。而最後一種可能，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，並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係，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。