66 communications of the acm | NovEmbER 2008 | vol. 51 | No. 11 review articles The past decade has witnessed a coming-together othe technological networks that connect computers on the Internet and the social networks that have linked humans or millennia. Beyond the artiacts thathave sprung rom this development—sites such as acebook, LinkedIn, MySpace, Wikipedia, digg, del. icio.us, YouTube, and fickr—there is a broader process at work, a growing pattern omovement through online spaces to orm connections with others, build virtual communities, and engage in sel-expression. Even as these new media have led to changes in our styles ocommunication, they have also remained governed by longstanding principles ohuman social interaction—principles that can nowbe observed and quantied at unprec- edented levels oscale and resolution through the data being generated bythese online worlds. Like time-lapse video or photographs through a micro- scope, these images osocial networks oer glimpses oeveryday lie rom an unconventional vantage point— images depicting phenomena such as the fow oinormation through an organization or the disintegration oa social group into rival actions. Sci- ence advances whenever we can take something that was once invisible and make it visible; and this is now takingplace with regard to social networks and social processes. Collecting social-network data has traditionally been hard work, requir- ing extensive contact with the group opeople being studied; and, given the practical considerations, research eorts have generally been limited to groups otens to hundreds oindi- viduals. Social interaction in online settings, on the other hand, leaves ex- tensive digital traces by its very nature. At the scales otens omillions oin- dividuals and minute-by-minute time granularity, we can replay and watch the ways in which people seek out con- nections and orm riendships on a site like Facebook or how they coordinate with each other and engage in creative expression on sites like Wikipedia and fickr. We can observe a news story sud- denly catching the attention omillions oreaders or witness how loomingclouds ocontroversy gather around a community obloggers. These are part othe ephemeral dynamics oor- dinary lie, now made visible through their online maniestations. As such, we are witnessing a revolution in the measurement ocollective human t c v rg s l d t l g l n w rk Doi:10.1145/1400214.1400232 Internet-based data on human interaction connects scientifc inquiry like never beore. BY Jon KLeinBeRG f a C e b o o K v i s u a l i z a t i o n : n e x u s f r i e n d G r a p h e r ( n e x u s . l u d i o s . n e t ) b y i v a n K o z i K The Nexus friend grapher application, createdby Ivan Kozik, allows Facebook account holders to generate graphs illustrating their social network of friends. The resulting spheres not onlydemonstrate how friends are connected, but also indicate the interests shared by different groups of friends. For more informatio n, or to create a graph, visit http://nex us.ludios.net.
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The past decade has witnessed a coming-together o the technological networks that connect computerson the Internet and the social networks that havelinked humans or millennia. Beyond the artiacts that have sprung rom this development—sites such asacebook, LinkedIn, MySpace, Wikipedia, digg, del.icio.us, YouTube, and fickr—there is a broader processat work, a growing pattern o movement throughonline spaces to orm connections with others, build
virtual communities, and engage in sel-expression.Even as these new media have led to changes in our
styles o communication, they have also remained
governed by longstanding principles o human social
interaction—principles that can now
be observed and quantied at unprec-
edented levels o scale and resolutionthrough the data being generated by these online worlds. Like time-lapse
video or photographs through a micro-
scope, these images o social networksoer glimpses o everyday lie rom
an unconventional vantage point—
images depicting phenomena suchas the fow o inormation through an
organization or the disintegration o
a social group into rival actions. Sci-ence advances whenever we can take
something that was once invisible andmake it visible; and this is now taking
place with regard to social networksand social processes.
Collecting social-network data has
traditionally been hard work, requir-ing extensive contact with the group
o people being studied; and, given
the practical considerations, researcheorts have generally been limited to
groups o tens to hundreds o indi-
viduals. Social interaction in onlinesettings, on the other hand, leaves ex-
tensive digital traces by its very nature. At the scales o tens o millions o in-
dividuals and minute-by-minute timegranularity, we can replay and watch
the ways in which people seek out con-
nections and orm riendships on a sitelike Facebook or how they coordinate
with each other and engage in creative
expression on sites like Wikipedia andfickr. We can observe a news story sud-
denly catching the attention o millions
o readers or witness how looming clouds o controversy gather around
a community o bloggers. These arepart o the ephemeral dynamics o or-
dinary lie, now made visible throughtheir online maniestations. As such,
we are witnessing a revolution in the
measurement o collective human
t
cvrg sl dtlgl
nwrk
Doi:10.1145/1400214.1400232
Internet-based data on human interactionconnects scientifc inquiry like never beore.
BY Jon KLeinBeRG
The Nexus friend grapher application, created
by Ivan Kozik, allows Facebook account holders
to generate graphs illustrating their social
network of friends. The resulting spheres not only
acting as highly connected “hubs.”3 Another principle, also a key issue
in sociology, is the notion o “triadic
closure:” links are much more likely
to orm between two people when they have a riend in common.34 Recent
work using email logs has providedsome o the rst concrete measure-
ments o the eect o triadic closure in
a social-communication network.24
Further principles have begun to
emerge rom recent studies o social and
inormation networks over time, includ-ing “densication eects,” in which the
number o links per node increases as
the network grows, and “shrinking di-
ameters,” in which the number o stepsin the shortest paths between nodes can
actually decrease even as the total num-ber o nodes is increasing.27
It is also intriguing to ask whether
machine-learning techniques can beeective at predicting the outcomes
o social processes rom observations
o their early stages. Problems here in-clude the prediction o new links, the
participation o people in new activ-
ities, the eectiveness o groups at
collective problem-solving, and thegrowth o communities over time.4,
16, 17, 18, 28, 37 Recent work by Salganik,
Dodds, and Watts raises the interest-ing possibility that the outcomes o
certain types o social-eedback eectsmay in act be inherently unpredict-able.36 Through an online experiment
in which participants were assignedto multiple, independently evolving
versions o a music-download site—
essentially, a set o articially con-structed “parallel universes” in which
copies o the site could develop inde-
pendently—Salganik et al. ound that when eedback was provided to users
about the popularity o the items being downloaded, early fuctuations in thepopularities o dierent items could
get locked in to produce very dierent
long-term trajectories o popularity.
Developing an expressive computa-tional model or this phenomenon is
an interesting open question.
Ultimately, across all these do-mains, the availability o such rich
and plentiul data on human interac-
tion has closed an important eedbackloop, allowing us to develop and evalu-
ate models o social phenomena at
large scales and to use these models
in the design o new computing ap-
plications. Such questions challenge
us to bridge styles o scientic inqui-ry—ranging rom subtle small-group
studies to computation on massive
datasets—that traditionally have hadlittle contact with each other. And they
are compelling questions in need o answers—because at their heart, they are about the human and technologi-
cal connections that link us all, and
the still-mysterious rhythms o thenetworks we inhabit.
akwldg
I thank the National Science Founda-
tion, the MacArthur Foundation, the
Cornell Institute or the Social Sci-
ences, Google, and Yahoo or their
support and the anonymous reviewerso this manuscript or their comments
and eedback.
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