Connected
The Surprising Power of
Our Social Networks and
How They Shape Our Lives

Nicholas A. Christakis, MD, PhD
James H. Fowler, PhD

Little, Brown and Company
New York Boston London

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Copyright © 2009 by Nicholas A. Christakis and James H. Fowler
All rights reserved. Except as permitted under the U.S. Copyright Act of 1976, no part of thispublication may be reproduced, distributed, or transmitted in any form or by any means, orstored in a database or retrieval system, without the prior written permission of the publisher.
Little, Brown and Company
Hachette Book Group237 Park Avenue, New York, NY 10017
www.hachettebookgroup.com
First Edition: September 2009
Little, Brown and Company is a division of Hachette Book Group, Inc. The Little,
Brown name and logo are trademarks of Hachette Book Group, Inc.
Library of Congress Cataloging-in-Publication Data
Christakis, Nicholas A.
Connected : the surprising power of our social networks and how they
shape our lives / Nicholas A. Christakis and James H. Fowler.—1st ed.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-316-03614-6 (hc) / 978-0-316-07258-8 (int’l ed)
1. Social networks. I. Fowler, James H. II. Title.
HM741.C46 2009
302.3—dc22
2009018349
10

9

8

7

6

5

4

3

2

1

rrd-inDesign by Meryl Sussman Levavi
Printed in the United States of America

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For Erika, Sebastian, Lysander, and Eleni
andfor Harla, Lucas, and Jay
to whom our connection is aeonian

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Contents

Prefaceix

1. In the Thick of It

3

2. When You Smile, the World Smiles with You

33

3. Love the One You’re With

61

4. This Hurts Me As Much As It Hurts You

95

5. The Buck Starts Here135

6. Politically Connected

172

7. It’s in Our Nature

210

8. Hyperconnected253

9. The Whole Is Great

287

Acknowledgments

307

Notes

311

Illustration Credits

327

Index

329

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Preface

ocial networks are intricate things of beauty. They are soelaborate and so complex—and so ubiquitous, in fact—that one has to wonder what purpose they serve. Why are
we embedded in them? How do they form? How do they
work? How do they affect us?
I (Nicholas) have been animated by these questions for the better
part of the past ten years. I began by being interested in the simplest
social network of all: a pair of people, a dyad. Initially, the dyads I
studied were husbands and wives. As a physician caring for terminally ill patients and their families, I noticed the serious toll that a
loved one’s death had on a spouse. And I became interested in how
illness in one person might cause illness in another. For it seemed
to me that if people are interconnected, their health must also beinterconnected. If a wife falls ill or dies, her husband’s risk of deathassuredly rises. Eventually, I began to realize that there were all kindsof dyads I might study, such as pairs of siblings or pairs of friends orpairs of neighbors who are connected (not separated) by a backyard
fence.

S

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But the intellectual heart of the matter was not in these simple
arrangements. Instead, the key realization was that these dyads
agglomerate to form huge webs of ties stretching far into the distance. A man’s wife has a best friend who has a husband who hasa coworker who has a sibling who has a friend, and so on and soforth. These chains branch like lightning bolts, forming intricate patterns throughout human society. The situation, it seemed, was much
more complicated. With every step away from an individual in asocial network that we take, the number of ties to other humans, andthe complexity of the branching, rise very, very fast. As I reflectedon this problem, I began to read the work of other social scientists,from lonely German scholars at the turn of the twentieth century tovisionary sociologists in the 1970s, who had studied social networks
ranging in size from three to thirty people. But my interest lay insocial networks of three thousand or thirty thousand or even three
million people.
I realized that to study things of such complexity, I would makebetter progress if I worked with another investigator. As it turned
out, James Fowler, also at Harvard, was studying networks froma completely different perspective. James and I did not know eachother despite working in adjoining buildings on the same campus
for several years. In 2002 we were introduced by a mutual colleague,
political scientist Gary King. In other words, we started our journey
as friends of a friend. Gary thought we might have common intellectual interests, and he was right. Indeed, the very fact that we met
because of our social network illustrates a major point we want tomake about how and why social networks operate and how they
benefit us.
James had spent a number of years studying the origin of people’s
political beliefs and examining how one person’s attempt to solve asocial or political problem influenced others. How did humans cometogether to accomplish what they could not do on their own? And
he shared interests in other topics that were a key part of the story:x84246 i-xiv 001-338 r4sr.indd x

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Preface

altruism and goodness, both of which are essential for social networks to grow and endure.
Together, as we began to think about the idea that people are connected in vast social networks, we realized that social influence does
not end with the people we know. If we affect our friends, and theyaffect their friends, then our actions can potentially affect people wehave never met. We began by studying various health effects. We discovered that if your friend’s friend’s friend gained weight, you gained
weight. We discovered that if your friend’s friend’s friend stopped
smoking, you stopped smoking. And we discovered that if yourfriend’s friend’s friend became happy, you became happy.
Eventually, we realized that there were fundamental rules thatgoverned both the formation and the operation of social networks.
We concluded that if we were going to study how networks function,
we also had to understand how they are assembled. One cannot, forexample, be friends with absolutely anybody. People are constrainedby geography, socioeconomic status, technology, and even genes tohave certain kinds of social relationships and to have a certain number of them. The key to understanding people is understanding theties between them; therefore, it was to the ties that we turned our
focus.
Our interest in these topics paralleled the interests of many other
scholars who have advanced the mathematics and science of networks
over the past ten years. As we began to study human connections,
we encountered engineers studying networks of power stations,
neuroscientists studying networks of neurons, geneticists studying networks of genes, and physicists studying networks of darnnear everything. Their networks might be pretty too, we thought,
but ours were more interesting: much more complicated and much
more consequential. After all, the nodes in our networks are thinking
human beings. They can make decisions, potentially changing their
networks even while embedded in them and being affected by them.
A network of humans has a special kind of life of its own.

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Preface

Just as scientists have become interested in the underlying beautyand explanatory power of networks, the person on the street thinks
about them too. This is largely due to the appearance of the Internet
in people’s homes, which has given everyone a notion of how lotsof things might be interconnected. People began to speak colloquially about the “Net” and eventually the “World Wide Web” (not tomention the smash-hit movie The Matrix). And they began to realizethat they were as interconnected as their computers. These connections have become explicitly social to the point that today nearly
everyone is familiar with social-network websites like Facebook andMySpace.
As we studied social networks more deeply, we began to thinkof them as a kind of human superorganism. They grow and evolve.
All sorts of things flow and move within them. This superorganism
has its own structure and a function, and we became obsessed with
understanding both.
Seeing ourselves as part of a superorganism allows us to understand our actions, choices, and experiences in a new light. If we areaffected by our embeddedness in social networks and influenced byothers who are closely or distantly tied to us, we necessarily lose
some power over our own decisions. Such a loss of control can provoke especially strong reactions when people discover that theirneighbors or even strangers can influence behaviors and outcomesthat have moral overtones and social repercussions. But the flip sideof this realization is that people can transcend themselves and theirown limitations. In this book, we argue that our interconnection is
not only a natural and necessary part of our lives but also a force forgood. Just as brains can do things that no single neuron can do, so
can social networks do things that no single person can do.
For decades, even centuries, serious human concerns, such aswhether a person will live or die, be rich or poor, or act justly or
unjustly, have been reduced to a debate about individual versus collective responsibility. Scientists, philosophers, and others who study

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society have generally divided into two camps: those who think individuals are in control of their destinies, and those who believe thatsocial forces (ranging from a lack of good public education to thepresence of a corrupt government) are responsible for what happens
to us.
However, we think that a third factor is missing from this debate.
Given our research and our own diverse experiences in life—frommeeting our spouses to meeting each other, from caring for terminally ill patients to building latrines in poor villages—we believe that
our connections to other people matter most, and that by linking thestudy of individuals to the study of groups, the science of social networks can explain a lot about human experience. This book focuseson our ties to others and how they affect emotions, sex, health, politics, money, evolution, and technology. But most of all it is about
what makes us uniquely human. To know who we are, we must
understand how we are connected.

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c h apter 1

In the Thick of Itn the mountain village of Levie, Corsica, during the 1840s,
Anton-Claudio Peretti became convinced that his wife,
Maria-Angelina, was having an affair with another man
and that, even worse, their daughter was not his child.
Maria told Anton that she was going to leave him, and she madepreparations to do so with her brother, Corto. That very evening,
Anton shot his wife and daughter to death and fled to the mountains.
The bereft Corto sorely wanted to kill Anton, but he could not findhim. In a bit of violent symmetry that seemed sensible to residents of
the area, Corto instead killed Anton’s brother, Francesco, andnephew, Aristotelo.
It did not end there. Five years later, Giacomo, brother of thedeceased Aristotelo, avenged the deaths of his brother and father bykilling Corto’s brother. Giacomo wanted to kill Corto’s father too,but he had already died of natural causes, denying Giacomo the satisfaction.1 In this cascade of death, Giacomo and Corto’s brother wereconnected by quite a path: Giacomo was the son of Francesco, who
was the brother of Anton, who was married to Maria, who was theI

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Connected

sister of Corto, whose brother was the target of Giacomo’s murderous wrath.
Such behavior is not restricted to historically or geographicallydistant places. Here is another example, closer to home: Not long
before the summer of 2002 in St. Louis, Missouri, Kimmy, an exotic
dancer, left a purse containing $900 in earnings with a friend while
she was busy. When she came back to reclaim it, her friend and thepurse were gone. But a week later, Kimmy’s cousin spotted the purse
thief’s partner at a local shop, and she called Kimmy. Kimmy raced
over with a metal pole. She viciously attacked this friend of her erstwhile friend. Later she observed with pride that she had “beat her[friend’s] partner’s ass. . . . I know I did something . . . [to get even]that’s the closest thing I could [do].”2
Cases like these are puzzling. After all, what did Anton’s brotherand nephew and Kimmy’s friend’s friend have to do with anything?
What possible sense is there in injuring or killing the innocent? Evenby the incomprehensible standards of murderous violence, what isthe point of these actions, taken one week or five years later? What
explains them?
We tend to think of such cases as quaint curiosities, like Appalachian feuds, or as backward practices, like the internecine violence
between Shiite and Sunni tribesmen or the cycle of killings in Northern Ireland or the reciprocating gang violence in American cities.
But this grim logic has ancient roots. It is not just that the impetus to revenge is ancient, nor even that such violence can expressgroup solidarity (“we are Hatfields, and we hate McCoys”), but that
violence—in both its minor and extreme forms—can spread throughsocial ties and has done so since humans emerged from the Africansavanna. It can spread either in a directed fashion (retaliating against
the perpetrators) or in a generalized fashion (harming nondisputants
nearby). Either way, however, a single murder can set off a cascade ofkillings. Acts of aggression typically diffuse outward from a starting
point—like a bar fight that begins when one man swings at another484246 i-xiv 001-338 r4sr.indd 4

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In the Thick of It

who ducks, resulting in a third man getting hit, and soon (in what
has become a cliché precisely because it evokes deep-seated notionsof unleashed aggression) punches are flying everywhere. Sometimes
these epidemics of violence, whether in Mediterranean villages orurban gangs, can persist for decades.3
Notions of collective guilt and collective revenge that underlie
cascades of violence seem strange only when we regard responsibility as a personal attribute. Yet in many settings, morality resides ingroups rather than in individuals. And a further clue to the collective nature of violence is that it tends to be a public, not a private,phenomenon. Two-thirds of the acts of interpersonal violence inthe United States are witnessed by third parties, and this fraction
approaches three-fourths among young people.4
Given these observations, perhaps the person-to-person spreadof violence should not surprise us. Just as it is often said that “thefriend of my friend is my friend” and “the enemy of my enemy is
my friend,” so too the friend of my enemy is my enemy. These aphorisms encapsulate certain truths about animosity and affection, butthey also convey a fundamental aspect of our humanity: our connection. While Giacomo and Kimmy acted alone, their actions show justhow easily responsibility and retaliation can diffuse from person toperson to person across social ties.
In fact, we do not even have to search for complicated paths
across which violence spreads, because the initial step, from the very
first person to the next, accounts for most of the violence in our society. In trying to explain violence, it is myopic to focus solely on theperpetrator—his frame of mind, his finger on the trigger—because
murder is rarely a random act between strangers. In the UnitedStates, 75 percent of all homicides involve people who knew eachother, often intimately, prior to the murder. If you want to know
who might take your life, just look at the people around you.
But your social network also includes those who might save yourlife. “On March 14, 2002, I gave my right kidney to my best friend’s

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Connectedhusband,” Cathy would later note in an online forum that chronicles
the experiences of people who become “living donors” of organs.
The summer before, during a heartfelt chat, Cathy had learned thather friend’s husband’s renal failure had worsened and that he neededa kidney transplant in order to survive. Overcome with the desire tohelp, Cathy underwent a series of medical and psychological evaluations, getting more and more excited as she passed each one andmoved closer to her goal of donating one of her kidneys. “The experience has been the most rewarding of my life,” she wrote. “I am so
grateful that I was able to help my best friend’s husband. His wife
has her husband back. His sons have their dad back. . . . It’s a win-win
situation. We all win. I gave the gift of life.”5Similar stories abound, and such “directed donations” of organs
can even come to involve people who have rather tenuous connections, a Starbucks clerk and his longtime customer, for example.
There can even be organ-donation cascades that loosely resemble the
Perettis’ murder cascade. John Lavis, a sixty-two-year-old residentof the town of Mississauga, Ontario, father of four and grandfatherof three, was dying of heart failure in 1995. His heart had failed during triple-bypass surgery, and he was placed on a temporary artificial
heart. In a stroke of unbelievable good fortune, a donor heart wastransplanted into him just eight days later when he was on the brinkof death. His daughter recalled: “We were a family of immense gratitude. . . . [My father] received the biggest gift he will ever receive—hislife was given back to him.” Motivated by this experience, Lavis’schildren all signed organ-donor cards, thinking that this symmetrical
act was the least they could do. Then in 2007, Lavis’s son Dan died ina work-related accident. Eight people benefited from Dan’s decision
to donate his organs. The woman who received his heart later wrote
to the Lavis family, thanking them for “giving her a new life.”6 The
same year in the United States, a similar cascade an amazing ten links
long took place between unrelated living kidney donors (albeit with
explicit medical coordination), saving many lives along the way.7

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In the Thick of It

Social-network ties can—and, as we will see, usually do—convey
benefits that are the very opposite of violence. They can be conduits
for altruistic acts in which individuals pay back a debt of gratitude
by paying it forward. The role that social connections can play in the
spread of both good and bad deeds has even prompted the creation ofnovel strategies to address social problems. For example, programs inseveral U.S. metropolitan areas involve teams of “violence interrupters.” These streetwise individuals, often former gang members, try tostop the killing by attempting to break the cycle of transmission. Theyrush to the bedsides of victims or to the homes of victims’ families andfriends, encouraging them not to seek revenge. If they can persuade
just one person not to be violent, quite a few lives can be saved.
Our connections affect every aspect of our daily lives. Rare events
such as murder and organ donation are just the tip of the iceberg. How
we feel, what we know, whom we marry, whether we fall ill, how muchmoney we make, and whether we vote all depend on the ties that bind us.
Social networks spread happiness, generosity, and love. They are always
there, exerting both subtle and dramatic influence over our choices,
actions, thoughts, feelings, even our desires. And our connections do not
end with the people we know. Beyond our own social horizons, friendsof friends of friends can start chain reactions that eventually reach us,
like waves from distant lands that wash up on our shores.

Bucket Brigades and Telephone Trees
Imagine your house is on fire. Luckily, a cool river runs nearby. But
you are all alone. You run back and forth to the river, bucket in hand,
toting gallon after gallon of water to splash on your burning home.
Unfortunately, your efforts are useless. Without some help, you will
not be able to carry water fast enough to outpace the inferno.
Now suppose that you are not alone. You have one hundred
neighbors, and, lucky for you, they all feel motivated to help. And

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Connectedeach one just happens to have a bucket. If your neighbors are sufficiently strong, they can run back and forth to the river, haphazardly
dumping buckets of water on the fire. A hundred people tossing
water on your burning house is clearly better than you doing it by
yourself. The problem is that once they get started your neighbors
waste a lot of time running back and forth. Some of them tire easily;
others are uncoordinated and spill a lot of water; one guy gets lost on
his way back to your house. If each person acts independently, thenyour house will surely be destroyed.
Fortunately, this does not happen because a peculiar form of socialorganization is deployed: the bucket brigade. Your hundred neighbors form a line from the river to your house, passing full buckets ofwater toward your house and empty buckets toward the river. Not
only does the bucket brigade arrangement mean that people do nothave to spend time and energy walking back and forth to the river;it also means that weaker people who might not be able to walk or
carry a heavy bucket long distances now have something to offer. A
hundred people taking part in a bucket brigade might do the work of
two hundred people running haphazardly.
But why exactly is a group of people arranged this way more
effective than the same group of people—or even a larger group—working independently? If the whole is greater than the sum of
its parts, how exactly does the whole come to be greater? Where doesthe “greater” part come from? It’s amazing to be able to increase theeffectiveness of human beings by as much as an order of magnitude
simply by arranging them differently. But what is it about combining people into groups with particular configurations that makes
them able to do more things and different things than the individuals
themselves?
To answer these questions, and before we get to the fun stuff, we
first need to explain a few basic terms and ideas of network theory.
These basic concepts set the stage for the individual stories and themore complicated ideas we will soon explore as we investigate the884246 i-xiv 001-338 r4sr.indd 8

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surprising power of social networks to affect the full spectrum of
human experience.
We should first clarify what we mean by a group of people. A groupcan be defined by an attribute (for example, women, Democrats, lawyers, long-distance runners) or as a specific collection of individuals towhom we can literally point (“those people, right over there, waiting to
get into the concert”). A social network is altogether different. Whilea network, like a group, is a collection of people, it includes something
more: a specific set of connections between people in the group. Theseties, and the particular pattern of these ties, are often more important
than the individual people themselves. They allow groups to do things
that a disconnected collection of individuals cannot. The ties explain
why the whole is greater than the sum of its parts. And the specificpattern of the ties is crucial to understanding how networks function.
The bucket brigade that saves a house is a very simple social network. It is linear and has no branches: each person (except the firstand last) is connected to two other people, the one in front and theone behind. For moving something like water long distances, thisis a good way to be organized. But the optimal organization of one
hundred people into a network depends very much on the task at
hand. The best pattern of connections between a hundred people toput out a fire is different from the best pattern for, say, achieving a
military objective. A company of one hundred soldiers is typicallyorganized into ten tightly interconnected squads of ten. This allows
each soldier to know all of his squad mates rather than just the grunt
in front of him and the grunt behind him. The military goes to great
lengths to help squad members know each other very well, so well infact that they are willing to give their lives for one another.
Consider still another social network: the telephone tree. Suppose
you need to contact a hundred people quickly to let them know that
school is canceled. Before modern communications and the Internet,
this was a challenge because there was no public source of up-to-theminute information that everyone could access from their homes

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Connected(though the ringing of church bells in the town square comes to mind).
Instead, each person needed to be contacted directly. The telephone
made this task much easier, but it was still a burden for one person to
make all one hundred calls. And even if someone set out to do this,it might take quite a while to get to the people at the end of the list,
by which time they may have already left home for school. Having asingle person make all the calls is both inefficient and burdensome.
Ideally, one person would set off a chain reaction so that everyone could be reached as quickly as possible and with the least burden on any particular individual. One option is to create a list andhave the person at the top of the list call the next person, the second
person call the third, and so on until everyone gets the message, as
in a bucket brigade. This would distribute the burden evenly, but itwould still take a really long time for the hundredth person to bereached. Moreover, if someone in the sequence was not home whencalled, everyone later in the list would be left in the dark.
An alternative pattern of connections is a telephone tree. The first
person calls two people, who each call two people, and so on until
everyone is contacted. Unlike the bucket brigade, the telephone tree
is designed to spread information to many people simultaneously, creating a cascade. The workload is distributed evenly among all groupmembers, and the problem caused by one person not being home islimited. Moreover, with a single call, one person can set off a chain of
events that could influence hundreds or thousands of other people—
just as the person who donated the heart that was transplanted into
John Lavis prompted another donation that saved eight more lives.
The telephone tree also vastly reduces the number of steps it takes
for information to flow among people in the group, minimizing thechance that the message will be degraded. This particular network
structure thus helps to both amplify and preserve the message. In fact,
within a few decades of the widespread deployment of home-based
phones in the United States, telephone trees were used for all sorts of
purposes. An article in the Los Angeles Times from 1957, for example,

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describes the use of a phone tree to mobilize amateur astronomers, aspart of the “Moonwatch System” of the Smithsonian AstrophysicalObservatory, to track American and Russian satellites.8
Alas, this same network structure also allows a single swindler
to cheat thousands of people. In Ponzi schemes, money flows “up”
a structure like a telephone tree. As new people are added to the
network, they send money to the people “above” them and thennew members are recruited “below” them to provide more money.
As time passes, money is collected from more and more people. In
what might be the biggest Ponzi scheme of all time, federal investigators discovered in 2008 that during the previous thirty years Bernie
Madoff had swindled $50 billion from thousands of investors. Like
the Corsican vendetta network we described earlier, Madoff’s investment network is the kind most of us would like to avoid.
The four different types of networks we have considered so far
are shown in the illustration. First is a group of one hundred people(each represented by a circle, or node) among whom there are noties. Next is a bucket brigade. Here, in addition to the one hundred
people, there are a total of ninety-nine ties between the membersof the group; every person (except the first and last) is connected
to two other people by a mutual tie (meaning that full and empty
buckets pass in both directions). In the telephone tree, there are one
hundred people and again ninety-nine ties. But here, everyone, withthe exception of the first and last people in the tree, is connected tothree other people, with one inbound tie (the person they get the callfrom) and two outbound ties (the people they make calls to). There
are no mutual ties; the flow of information is directional and so are
the ties between people. In a company of one hundred soldiers, eachmember of each squad knows every other member of the squad very
well; and each person has exactly nine ties. Here, there are one hundred people and 450 ties connecting them. (The reason there are notnine hundred ties is that each tie counts once for the two people itconnects.) In the drawing, we imagine that there are no ties between

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ConnectedUnconnected group

Bucket brigade

Telephone tree

Military squads

Four different ways to connect one hundred people. Each circle(“node”) represents a person, and each line (“tie”) a relationshipbetween two people. Lines with arrows indicate a directed relationship; in the telephone tree, one person calls another. Otherwise, ties
are mutual: in the bucket brigade, full and empty buckets travel inboth directions; in military squads, the connections between the soldiers are all two-way.

squads or, at least, that the ties within squads are much tighter than
the ties between squads. This is clearly an oversimplification, but it
illustrates still another point about communities in social networks.
A network community can be defined as a group of people who are

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much more connected to one another than they are to other groupsof connected people found in other parts of the network. The communities are defined by structural connections, not necessarily by
any particular shared traits.
In a very basic sense, then, a social network is an organized setof people that consists of two kinds of elements: human beings andthe connections between them. Unlike the bucket brigade, telephone
tree, and military company, however, the organization of naturalsocial networks is typically not imposed from the top. Real, everyday social networks evolve organically from the natural tendency ofeach person to seek out and make many or few friends, to have large
or small families, to work in personable or anonymous workplaces.
For example, in the next illustration, we show a network of 105
students in a single dormitory at an American university and thefriendship ties between them. On average, each student is connected
to six other close friends, but some students have only one friend, andothers have many. Moreover, some students are more embedded thanothers, meaning they have more connections to other people in the
network via friends or friends of friends. In fact, network visualization software is designed to place those who are more interconnectedin the center and those who are less interconnected at the periphery,
helping us to see each person’s location in the network. When yourfriends and family become better connected, it increases your level ofconnection to the whole social network. We say it makes you more
central because having better-connected friends literally moves you
away from the edges and toward the center of a social network. And
we can measure your centrality by counting not just the number ofyour friends and other contacts but also by counting your friends’
friends, and their friends, and so on. Unlike the bucket brigade where
everyone feels his position to be the same (“there’s a guy on my left
passing me buckets and a guy on my right to whom I give them—it
doesn’t matter where in the line I am”), here, people are located in
distinctly different kinds of places within the network.

13

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Connected

B

A
C
D

In this natural network of close friendships among 105 college students living in the same dormitory, each circle represents a student,
and each line a mutual friendship. Even though A and B both havefour friends, A’s four friends are more likely to know one another(there are ties between them), whereas none of B’s friends know eachother. A has greater transitivity than B. Also, even though C andD both have six friends, they have very different locations in thesocial network. C is much more central, and D is more peripheral;
C’s friends have many friends themselves, whereas D’s friends tend
to have few or no friends.

A network’s shape, also known as its structure or topology, is abasic property of the network. While the shape can be visualized,or represented, in different ways, the actual pattern of connections
that determines the shape remains the same regardless of how the
network is visualized. Imagine a set of five hundred buttons strewn
on the floor. And imagine that there are two thousand strings we canuse to connect the buttons. Next, imagine that we randomly selecttwo buttons and connect them with a string, knotting each button at
the end. Then we repeat this procedure, connecting random pairs of

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buttons one after another, until all the strings are used up. In the end,
some buttons will have many strings attached to them, and others, by
chance, will never have been picked and so will not be connected toanother button. Perhaps some groups of buttons will be connectedto each other but separated from other groups. These groups—even
those that consist of a single unconnected button—are called components of the network; when we illustrate networks, we frequently
represent only the largest component (in this case, the one with themost buttons).
If we were to select one button from one component and pick it
up off the floor, all other buttons attached to it, directly or indirectly,
would also be lifted into the air. And if we were to drop this mass of
buttons onto another spot on the floor, it would look different thanit did when we first picked it up. But the topology—which is a fundamental and intrinsic property of the network of buttons—would
be exactly the same, no matter how many times we picked up anddropped the mass of connected buttons. Each button has the same
relational position to other particular buttons that it had before; its
location in the network has not changed. Visualization software tries
to show this in two dimensions and to reveal the underlying topology by putting the most tangled buttons in the center and the least
connected ones on the edges. It’s as if you were trying to untangle
a gnarled set of Christmas-tree lights, and there were tendrils of thegnarled mess that you could pull out, and also a thicket of interknotted lights that remained in the center no matter how often you
turned the tangle over on the floor.
For numerous reasons we will explore, people come to occupy
particular spots in the naturally occurring and continuously evolvingsocial networks that surround us. Organic networks have a structure, complexity, function, spontaneity, and sheer beauty not foundin organized networks, and their existence provokes questions about
how they arise, what rules they obey, and what purpose they serve.

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Rules of Life in the Network
There are two fundamental aspects of social networks, whether
they are as simple as a bucket brigade or as complex as a large
multigenerational family, a college dormitory, an entire community, or the worldwide network that links us all. First, there is connection, which has to do with who is connected to whom. When agroup is constituted as a network, there is a particular pattern of ties
that connects the people involved, the topology. Moreover, ties arecomplicated. They can be ephemeral or lifelong; they can be casualor intense; they can be personal or anonymous. How we construct
or visualize a network depends on how we define the ties of interest. Most analyses emphasize ties to family, friends, coworkers, andneighbors. But there are all sorts of social ties and, thus, all sorts ofsocial networks. In fact, when things such as sexually transmitted
diseases or dollar bills flow through a network, this flow itself can
define the ties and hence the structure of a particular set of network
connections.
Second, there is contagion, which pertains to what, if anything,flows across the ties. It could be buckets of water, of course, but it
also could be germs, money, violence, fashions, kidneys, happiness,or obesity. Each of these flows might behave according to its own
rules. For example, fire cannot be transported in buckets toward
the river; germs cannot affect someone who is immune; and obesity,
which we will discuss in chapter 4, tends to spread faster between
people of the same sex.
Understanding why social networks exist and how they workrequires that we understand certain rules regarding connection andcontagion—the structure and function—of social networks. These
principles explain how ties can cause the whole to be greater than thesum of the parts.

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RULE 1: WE SHAPE OUR NETWORK

Humans deliberately make and remake their social networks all thetime. The primary example of this is homophily, the conscious or
unconscious tendency to associate with people who resemble us (theword literally means “love of being alike”). Whether it’s Hells Angels
or Jehovah’s Witnesses, drug addicts or coffee drinkers, Democrats
or Republicans, stamp collectors or bungee jumpers, the truth isthat we seek out those people who share our interests, histories, anddreams. Birds of a feather flock together.
But we also choose the structure of our networks in three important ways. First, we decide how many people we are connected to.
Do you want one partner for a game of checkers or many partners
for a game of hide-and-seek? Do you want to stay in touch withyour crazy uncle? Do you want to get married, or would you rather
play the field? Second, we influence how densely interconnected ourfriends and family are. Should you seat the groom’s college roommate next to your bridesmaid at the wedding? Should you throw aparty so all your friends can meet each other? Should you introduce
your business partners? And third, we control how central we areto the social network. Are you the life of the party, mingling witheveryone at the center of the room, or do you stay on the sidelines?
Diversity in these choices yields an astonishing variety of structures for the whole network in which we come to be embedded. And
it is diversity in these choices—a diversity that has both social andgenetic origins as we will see in chapter 7—that places each of us ina unique location in our own social network. Of course, sometimes
these structural features are not a matter of choice; we may live inplaces that are more or less conducive to friendship, or we may beborn into large or small families. But even when these social-network
structures are thrust upon us, they still rule our lives.
We actually know quite a bit about how people vary in termsof how many friends and social contacts they have and in how

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Connectedinterconnected they are. Yet, identifying who a person’s social contacts are can be a tricky business since people have many interactionsof varying intensities with all sorts of people. While a person may
know a few hundred people by sight and name, he will typicallybe truly close to only a few. One way social scientists identify suchclose individuals is to ask questions like, who do you discuss important matters with? Or, who do you spend your free time with? Whenanswering such questions, people will identify a heterogeneous mix
of friends, relatives, coworkers, schoolmates, neighbors, and others.
We recently put these questions to a sample of more than three
thousand randomly chosen Americans. And we found that the average American has just four close social contacts, with most having
between two and six. Sadly, 12 percent of Americans listed no one
with whom they could discuss important matters or spend free time.
At the other extreme, 5 percent of Americans had eight such people.
About half of the people listed as members of Americans’ intimategroups were said to be friends, but the other half included a wide
variety of different kinds of relationships, including spouses, partners, parents, siblings, children, coworkers, fellow members of clubs,
neighbors, and professional advisers and consultants. Sociologist
Peter Marsden has called this group of people that we all have a “corediscussion network.” In a national sample of 1,531 Americans studied
in the 1980s, he found that core-discussion-network size decreases as
we age, that there is no overall difference between men and womenin core-network size, and that those with a college degree have core
networks that are nearly twice as large as those who did not finishhigh school.9
Next, in our own work, we asked the respondents to tell us how
interconnected their social contacts were to each other. So if a person
said that Tom, Dick, Harry, and Sue were his friends, we asked him
if Tom knew Dick, if Tom knew Harry, if Tom knew Sue, if Dickknew Harry, and so on. We then used these answers to calculate theprobability that any two of a person’s friends were also friends with

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each other. This probability is an important property that we use tomeasure how tightly interwoven a network is.
If you know Alexi, and Alexi knows Lucas, and Lucas knowsyou, we say this relationship is transitive—the three people involved
form a triangle. Some people live in the thick of many transitive relationships (like person A in the illustration on page 14), while others
have friends who do not know each other (like person B). Thosewith high transitivity are usually deeply embedded within a single
group, while those with low transitivity tend to make contact withpeople from several different groups who do not know one another,making them more likely to act as a bridge between different groups.
Overall, we found that if you are a typical American, the probability that any two of your social contacts know each other is about
52 percent.
Although these measures characterize the networks we can see,they also tell us something about the networks we cannot see. In thevast fabric of humanity, each person is connected to his friends, family, coworkers, and neighbors, but these people are in turn connectedto their friends, family, coworkers, and neighbors, and so on endlessly into the distance, until everyone on earth is connected (prettymuch) to everyone else, one way or another. So whereas we thinkof our own network as having a more limited social and geographic
reach, the networks that surround each of us are actually very widelyinterconnected.
It is this structural feature of networks that underlies the common expression “it’s a small world.” It is often possible, through a
few connections from person to person, for an individual to discovera connection to someone else. A famous example (at least amongsocial scientists) was described in a paper first drafted in the 1950s
by two early figures in the study of social networks, Ithiel de Sola
Pool and Manfred Kochen. One of the authors overheard a patientin a hospital in a small town in Illinois say to a Chinese patient in theadjoining bed: “You know, I’ve only known one Chinese before in

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my life. He was——from Shanghai.” Whereupon the response cameback, “Why, that’s my uncle.”10 In fact, the authors did not tell us his
name, perhaps because they were worried that the reader, in a further
illustration of the small-world effect, would know him.
RULE 2: OUR NETWORK SHAPES US

Our place in the network affects us in turn. A person who has nofriends has a very different life than one who has many. For example,
we will see in chapter 4 that having an extra friend may create allkinds of benefits for your health, even if this other person doesn’t
actually do anything in particular for you.
One study of hundreds of thousands of Norwegian military conscripts provides a simple example of how the mere number of social
contacts (here, siblings) can affect you.11 It has been known for sometime that first-born children score a few points higher in terms ofintelligence than second-born children, who in turn score a bit higher
than third-born children. One of the outstanding questions in thisarea of investigation, however, has been whether these differences are
due to biological factors fixed at birth or to social factors that comelater. The study of Norwegian soldiers showed that simple featuresof social networks, such as family size and structure, are responsible
for the differences. If you are a second-born son whose older sibling
died while you were a child, your IQ increases and resembles the IQof a first-born child. If you are a third-born child and one of yourolder siblings died, your IQ resembles that of a second-born child;and if both of your older siblings died, then your IQ resembles thatof a first-born child.
Whether your friends and other social contacts are friends with
one another is also crucial to your experience of life. Transitivity canaffect everything from whether you find a sexual partner to whether
you commit suicide. The effect of transitivity is easily appreciatedby the example of how divorce affects a child. If a child’s parents
are married (connected) then they probably talk to each other, but

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if they get divorced (disconnected) they probably do not. Divorcemeans that communication often has to pass through the child (“Tellyour father not to bother picking you up next Saturday!”), and it ismuch harder to coordinate raising the child (“You mean your motherbought you ice cream too?”). What is remarkable is that even though
the child is still deeply connected to both parents, her relationshipwith each of them changes as a consequence of the divorce. Yet thesechanges result from the loss of a connection between the parents—a
connection the child has little to do with. The child still has two parents, but her life is different depending on whether or not they areconnected.
And how many contacts your friends and family have is also relevant. When the people you are connected to become better connected, it reduces the number of hops you have to take from person
to person to reach everyone else in the network. You become more
central. Being more central makes you more susceptible to whateveris flowing within the network. For example, person C in the figure on page 14 is more central than person D. Ask yourself which
person you would rather be if a hot piece of gossip were spreading;you should be person C. Now ask yourself which person you would
rather be if a deadly germ were spreading in the network; you shouldbe person D. And this is the case even though persons C and D eachhave the same number of social ties: they are each directly connected
to just six people. In later chapters, we will show how your centrality
affects everything from how much money you make to whether you
will be happy.
RULE 3: OUR FRIENDS AFFECT US

The mere shape of the network around us is not all that matters,of course. What actually flows across the connections is also crucial. A bucket brigade is formed not to make a pretty line for you
to look at while your house is burning but so that people can passwater to each other to douse the flames. And social networks are not

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Connectedjust for water—they transport all kinds of things from one person toanother.
As we will discuss in chapter 2, one fundamental determinantof flow is the tendency of human beings to influence and copy one
another. People typically have many direct ties to a wide variety ofpeople, including parents and children, brothers and sisters, spouses(and nice ex-spouses), bosses and coworkers, and neighbors andfriends. And each and every one of these ties offers opportunities
to influence and be influenced. Students with studious roommates
become more studious. Diners sitting next to heavy eaters eat more
food. Homeowners with neighbors who garden wind up with manicured lawns. And this simple tendency for one person to influenceanother has tremendous consequences when we look beyond our
immediate connections.
RULE 4: OUR FRIENDS’ FRIENDS’ FRIENDS AFFECT US

It turns out that people do not copy only their friends. They also copy
their friends’ friends, and their friends’ friends’ friends. In the children’s game telephone, a message is passed along a line by each childwhispering into the next child’s ear. The message each child receives
contains all the errors introduced by the child sharing it as well as
those introduced by prior children to whom the child is not directly
connected. In this way, children can come to copy others to whomthey are not directly tied. Similarly, every parent warns children not
to put money in their mouths: the money, we think, contains germs
from numerous people whose hands it has passed through, and notjust from the most recent pair of hands. Analogously, our friends andfamily can influence us to do things, like gain weight or show up at
the polls. But their friends and family can influence us too. This is an
illustration of hyperdyadic spread, or the tendency of effects to spreadfrom person to person to person, beyond an individual’s direct social
ties. Corto’s brother lost his life because of such spread.
It is easy to think about hyperdyadic effects when the network is

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a straight line—(“that guy three people down the line better pass thebucket, or we’re all going to be in big trouble”). But how on earth
can they be understood in a natural social network such as the college students in the illustration on page 14, or complex networks ofthousands of people with all kinds of crosscutting paths stretching
far beyond the social horizon (as we will consider later)? To decipher
what is going on, we need two kinds of information. First, we must
look beyond simple, sequential dyads: we need to know about individuals and their friends, their friends’ friends, their friends’ friends’
friends, and so on. And we can only get this information by observing
the whole network at once. It has just recently become possible to do
this on a large scale. Second, if we want to observe how things flowfrom person to person to person, then we need information about
the ties and the people they connect at more than one point in time,otherwise we have no hope of understanding the dynamic propertiesof the network. It would be like trying to learn the rules of an unfamiliar sport by looking at a single snapshot of a game.
We will consider many examples and varieties of hyperdyadic
spread, but we can set the stage with a simple one. The usual way wethink about contagion is that if one person has something and comes
into contact with another person, that contact is enough for the second person to get it. You can become infected with a germ (the moststraightforward example) or with a piece of gossip or information(a less obvious example). Once you get infected by a single person,
additional contact with others is generally redundant. For example, if
you have been told accurately that stock XYZ closed at $50, anotherperson telling you the same thing does not add much. And you canpass this information on to someone else all by yourself.
But some things—like norms and behaviors—might not spreadthis way. They might require a more complex process that involves
reinforcement by multiple social contacts. If so, then a network
arranged as a simple line, like a bucket brigade, might not support
transmission of more complicated phenomena. If we wanted to get

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people to quit smoking, we would not arrange them in a line and get
the first one to quit and tell him to pass it on. Rather, we would surround a smoker with multiple nonsmokers, perhaps in a squad.
Psychologist Stanley Milgram’s famous sidewalk experimentillustrates the importance of reinforcement from multiple people.12
On two cold winter afternoons in New York City in 1968, Milgram
observed the behavior of 1,424 pedestrians as they walked along a
fifty-foot length of street. He positioned “stimulus crowds,” ranging
in size from one to fifteen research assistants, on the sidewalk. On
cue, these artificial crowds would stop and look up at a window on
the sixth floor of a nearby building for precisely one minute. There
was nothing interesting in the window, just another guy working for
Milgram. The results were filmed, and assistants later counted thenumber of people who stopped or looked where the stimulus crowd
was looking. While 4 percent of the pedestrians stopped alongsidea “crowd” composed of a single individual looking up, 40 percent
stopped when there were fifteen people in the stimulus crowd. Evidently, the decisions of passersby to copy a behavior were influenced
by the size of the crowd exhibiting it.
An even larger percentage of pedestrians copied the behavior
incompletely: they looked up in the direction of the stimulus crowd’s
gaze but did not stop. While one person influenced 42 percent ofpassersby to look up, 86 percent of the passersby looked up if fifteen people were looking up. More interesting than this difference,
however, was that a stimulus crowd of five people was able to induce
almost as many passersby to look up as fifteen people did. That is,in this setting, crowds larger than five did not have much more of aneffect on the actions of passing individuals.
RULE 5: THE NETWORK HAS A LIFE OF ITS OWNSocial networks can have properties and functions that are neither controlled nor even perceived by the people within them.
These properties can be understood only by studying the whole

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group and its structure, not by studying isolated individuals. Simple
examples include traffic jams and stampedes. You cannot understand a
traffic jam by interrogating one person fuming at the wheel of his car,even though his immobile automobile contributes to the problem.
Complex examples include the notion of culture, or, as we shall see,the fact that groups of interconnected people can exhibit complicated,shared behaviors without explicit coordination or awareness.
Many of the simple examples can be understood best if we completely ignore the will and cognition of the individuals involved andtreat people as if they were “zero-intelligence agents.” Consider thehuman waves at sporting events that first gained worldwide noticeduring the 1986 World Cup in Mexico. In this phenomenon, originally called La Ola (“the wave”), sequential groups of spectators leap
to their feet and raise their arms, then quickly drop back to a seatedposition. The effect is quite dramatic. A group of physicists who usually study waves on the surface of liquids were sufficiently intriguedthat they decided to study a collection of filmed examples of La Olain enormous soccer stadiums; they noticed that these waves usuallyrolled in a clockwise direction and consistently moved at a speed oftwenty “seats per second.”13
To understand how such human waves start and propagate, thescientists employed mathematical models of excitable media thatare ordinarily used to understand inanimate phenomena such as the
spread of a fire through a forest or the spread of an electrical signal
through cardiac muscle. An excitable medium is one that flips fromone state to another (like a tree that is either on fire or not) dependingon what others around it are doing (are nearby trees on fire?). And
these models yielded accurate predictions of the social phenomenon,suggesting that La Ola could be understood even if we knew nothing about the biology or psychology of humans. Indeed, the wave
cannot be understood by studying the actions of a single individual
standing up and sitting down. It is not orchestrated by someone witha megaphone atop a cooler. It has a life of its own.

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Mathematical models of flocks of birds and schools of fish andswarms of insects that move in unison demonstrate the same point:
there is no central control of the movement of the group, but thegroup manifests a kind of collective intelligence that helps all within
it to flee or deter predators. This behavior does not reside within
individual creatures but, rather, is a property of groups. Examinationof flocks of birds “deciding” where to fly reveals that they move in a
way that accounts for the intentions of all the birds, and, even more
important, the direction of movement is usually the best choice forthe flock. Each bird contributes a bit, and the flock’s collective choice
is better than an individual bird’s would be.14 Similar to La Ola andto flocking birds, social networks obey rules of their own, rules thatare distinct from the people who form them. But now, people are nothaving fun in a stadium: they are donating organs or gaining weightor feeling happy.
In this regard, we say that social networks have emergent properties.
Emergent properties are new attributes of a whole that arise from theinteraction and interconnection of the parts. The idea of emergencecan be understood with an analogy: A cake has a taste not found in any
one of its ingredients. Nor is its taste simply the average of the ingredients’ flavors—something, say, halfway between flour and eggs. It ismuch more than that. The taste of a cake transcends the simple sumof its ingredients. Likewise, understanding social networks allows us
to understand how indeed, in the case of humans, the whole comes tobe greater than the sum of its parts.

Six Degrees of Separation andThree Degrees of Influence
Stanley Milgram masterminded another, much more famous experiment showing that people are all connected to one another by anaverage of “six degrees of separation” (your friend is one degree

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from you, your friend’s friend is two degrees, and so on). Milgram’s
experiment, conducted in the 1960s, involved giving a few hundred
people who lived in Nebraska a letter addressed to a businessman in
Boston, more than a thousand miles away.15 They were asked to send
the letter to somebody they knew personally. The goal was to get it
to someone they thought would be more likely than they to have apersonal relationship with the Boston businessman. And the numberof hops from person to person that the letter took to reach the target was tracked. On average, six hops were required. This amazing
fact initiated a whole set of investigations into the small-world effectoriginally characterized by de Sola Pool and Kochen, and it enteredpopular culture too, with John Guare’s play Six Degrees of Separation and even the trivia game Six Degrees of Kevin Bacon.
But some academics were skeptical. For instance, as far apart as
Nebraska and Boston might be (both geographically and culturally),
they were both inside the United States. So in 2002, physicist-turnedsociologist Duncan Watts and his colleagues Peter Dodds and Roby
Muhamad decided to replicate Milgram’s experiment on a global scaleusing e-mail as the mode by which people communicated.16 They
recruited more than ninety-eight thousand subjects (mostly from theUnited States) to send a message to “targets” around the world byforwarding the e-mail to someone each subject knew who might inturn know the targeted person. Each subject was randomly assigned
one target from a list of eighteen possible targets in thirteen countries. The targets included a professor at an Ivy League university,
an archival inspector in Estonia, a technology consultant in India, a
policeman in Australia, and a veterinarian in the Norwegian army—
quite a motley crew. Once again—astonishingly—it took roughly six
steps (on average) to get the e-mail to each targeted person, replicating Milgram’s original estimate of just how small the world is.
However, just because we are connected to everyone else by six
degrees of separation does not mean that we hold sway over all ofthese people at any social distance away from us. Our own research

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has shown that the spread of influence in social networks obeys what
we call the Three Degrees of Influence Rule. Everything we do or
say tends to ripple through our network, having an impact on ourfriends (one degree), our friends’ friends (two degrees), and even ourfriends’ friends’ friends (three degrees). Our influence gradually dissipates and ceases to have a noticeable effect on people beyond thesocial frontier that lies at three degrees of separation. Likewise, we
are influenced by friends within three degrees but generally not by
those beyond.
The Three Degrees Rule applies to a broad range of attitudes,
feelings, and behaviors, and it applies to the spread of phenomena as
diverse as political views, weight gain, and happiness. Other scholars
have documented that among networks of inventors, innovative ideas
seem to diffuse to three degrees, so that an inventor’s creativity influences his colleagues, his colleagues’ colleagues, and his colleagues’
colleagues’ colleagues. And word-of-mouth recommendations foreveryday concerns (like how to find a good piano teacher or how tofind a home for a pet) tend to spread three degrees too.
There are three possible reasons our influence is limited. First,
like little waves spreading out from a stone dropped into a still pond,
the influence we have on others may eventually peter out. The stone
displaces a certain volume of water as it is dropped, and the energy
in the wave dissipates as it spreads out. One way to think about thissocially is that there is decay in the fidelity of information as it istransmitted, as in the child’s game of telephone. So, if you quit smoking or endorse a particular political candidate, by the time this information reaches your friends’ friends’ friends’ friend, that person may
no longer have accurate or reliable information about what you actually did. We call this the intrinsic-decay explanation.
Second, influence may decline because of an unavoidable evolution in the network that makes the links beyond three degrees
unstable. Ties in networks do not last forever. Friends stop being
friends. Neighbors move. Spouses divorce. People die. The only way

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to lose a direct connection to someone you know is if the tie between
you disappears. But for a person three degrees removed from you,any of three ties could be cut and you would lose at least one pathway between you. Hence, on average, we may not have stable ties
to people at four degrees of separation given the constant turnoverin ties all along the way. Consequently, we do not influence nor are
we influenced by people at four degrees and beyond. We call this the
network-instability explanation.
Third, evolutionary biology may play a part. As we will discuss inchapter 7, humans appear to have evolved in small groups in which
everyone would have been connected to everyone else by threedegrees or less. It is indeed useful to know whether anyone in ourgroup has it in for us or is our ally, or whether others need our help
or might help us. And it is useful to influence others in our group to
do what we do. But we have not lived in large groups long enoughfor evolution to have favored people who can extend their influence
beyond three degrees. Put another way, we may not be able to influence people four degrees removed from us because, in our hominid
past, there was no one who was four degrees removed from us. We
call this the evolutionary-purpose explanation.
It seems likely that all these factors play a role. But no matter thereasons, the Three Degrees Rule appears to be an important part of
the way human social networks function, and it may continue toconstrain our ability to connect, even though technology gives us
access to so many more people.
While this inherent limit may seem, well, limiting (who doesn’twant to rule the world?), we should remember how small the worldis. If we are connected to everyone else by six degrees and we can
influence them up to three degrees, then one way to think about ourselves is that each of us can reach about halfway to everyone else on
the planet.
Moreover, even when restricted to three degrees, the extent of oureffect on others is extraordinary. The way natural social networks are

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Connectedstructured means that most of us are connected to thousands of people.
For example, suppose you have twenty social contacts, including fivefriends, five coworkers, and ten family members, and each of them inturn has similar numbers of friends and family (to make things simple, let’s assume they are not the same contacts as yours). That means
you are indirectly connected to four hundred people at two degrees
of separation. And your influence doesn’t stop there; it goes one more
step to the twenty friends and family of each of those people, yielding
a total of 20 × 20 × 20 people, or eight thousand people who are threedegrees removed from you. That would include every single personin the small Oklahoma town where James grew up.
So while the observation that there are six degrees of separation
between any two people applies to how connected we are, the observation that there are three degrees of influence applies to how contagious we are. These properties, connection and contagion, are thestructure and function of social networks. They are the anatomy andphysiology of the human superorganism.

Connected
Most of us are already aware of the direct effect we have on ourfriends and family; our actions can make them happy or sad, healthyor sick, even rich or poor. But we rarely consider that everything wethink, feel, do, or say can spread far beyond the people we know.
Conversely, our friends and family serve as conduits for us to be
influenced by hundreds or even thousands of other people. In a kindof social chain reaction, we can be deeply affected by events we do
not witness that happen to people we do not know. It is as if we canfeel the pulse of the social world around us and respond to its persistent rhythms. As part of a social network, we transcend ourselves,for good or ill, and become a part of something much larger. We areconnected.

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In the Thick of It

Our connectedness carries with it radical implications for the way
we understand the human condition. Social networks have value precisely because they can help us to achieve what we could not achieveon our own. In the next few chapters, we will show how networks
influence the spread of joy, the search for sexual partners, the maintenance of health, the functioning of markets, and the struggle fordemocracy. Yet, social-network effects are not always positive.
Depression, obesity, sexually transmitted diseases, financial panic,
violence, and even suicide also spread. Social networks, it turns out,
tend to magnify whatever they are seeded with.
Partly for this reason, social networks are creative. And whatthese networks create does not belong to any one individual—it isshared by all those in the network. In this way, a social network islike a commonly owned forest: we all stand to benefit from it, but wealso must work together to ensure it remains healthy and productive.
This means that social networks require tending, by individuals, bygroups, and by institutions. While social networks are fundamentally and distinctively human, and ubiquitous, they should not betaken for granted.
If you are happier or richer or healthier than others, it may havea lot to do with where you happen to be in the network, even if you
cannot discern your own location. And it may have a lot to do withthe overall structure of the network, even if you cannot control thatstructure at all. And in some cases, the process feeds back to the network itself. A person with many friends may become rich and thenattract even more friends. This rich-get-richer dynamic means social
networks can dramatically reinforce two different kinds of inequality in our society: situational inequality (some are better off socioeconomically) and positional inequality (some are better off in termsof where they are located in the network).
Lawmakers have not yet considered the consequences of positional inequality. Still, understanding the way we are connected isan essential step in creating a more just society and in implementing

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Connectedpublic policies affecting everything from public health to the economy. We might be better off vaccinating centrally located individuals rather than weak individuals. We might be better off persuading
friends of smokers of the dangers of smoking rather than targetingsmokers. We might be better off helping interconnected groups ofpeople to avoid criminal behavior rather than preventing or punishing crimes one at a time.
The powerful effect of social networks on individual behaviors
and outcomes suggests that people do not have complete control
over their own choices. Interpersonal influence in social networks
therefore raises moral questions. Our connections to others affectour capacity for free will. How much blame does Giacomo in Corsica deserve for his actions, and how much credit does Dan Lavis in
Ontario deserve for his? If they acted merely as links in a chain, how
can we understand their freedom to choose their actions at all?
Some scholars explain collective human behavior by studying the
choices and actions of individuals. Others dispense with individuals and focus exclusively on groups formed by social class, race, or
political party affiliation, each with collective identities that cause
people in these groups to mysteriously and magically act in concert.
The science of social networks provides a distinct way of seeing theworld because it is about individuals and groups, and about how theformer actually become the latter.
If we want to understand how society works, we need to fill inthe missing links between individuals. We need to understand howinterconnections and interactions between people give rise to wholly
new aspects of human experience that are not present in the individuals themselves. If we do not understand social networks, we cannot
hope to fully understand either ourselves or the world we inhabit.

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