[Applause]
imagine seeing a university campus from
a helicopter but with detailed data
about every single individual so how
they move around who they’re hanging out
with and also all the online
communication mapped out that’s what you
need to really understand human social
networks now as a young researcher I
worked at US universities like Harvard
and Northeastern crunching data about
phone calls and we were trying to find
out how to analyze the network of all
the phone calls made by an entire nation
alright so that’s millions of
individuals and it’s billions of phone
calls but those billions of phone calls
they weren’t enough for me and the
reason is that I’ve become obsessed with
creating the best data set about
networks in the world I had this idea
that we could take our understanding of
social networks to the next level if we
could just zoom out and collect data
about an entire social system I imagined
this social system as a kind of massive
anthill teeming with activity you see
the thing is that as wonderful as it
sounds with all those billions of phone
calls they don’t say much about how
humans really connect to one another
only a fraction of our communication
happens over the phone so to make this
obsession of mine a reality I found this
group of individuals with lots of social
activity between them all the freshmen
at my university the Technical
University of Denmark
I got started on mapping out all their
communication and all their networks and
to do that I went out and I purchased
1,000 identical top-of-the-line
smartphones and we installed custom
software on each one to measure the
networks and as in the side that is a
lot of phones to install custom software
on of course these phones that I gave to
the students they would give me
information about the phone calls and
the text messages but the smart phone
also knows who you’re hanging out with
what’s going on in your Facebook feed
and much more and as another side can I
tell you something at this point I
wasn’t sleeping very well and the thing
that was keeping me awake was the weight
the sheer responsibility of this huge
machine that we were building to observe
this human anthill ok the budget was
tens of millions
I put an entire team of people to work
countless hours of effort and
collaborators depending on me and
frankly I had no idea what I was doing
because how could I no one had ever done
anything like this on a scale like this
before and the most scary thing was that
I had to come up with some kind of
fantastic scientific insight and in
research the result is the only novel if
you don’t know what it is ahead of time
so I was seriously worried that I made
too big a gamble so one day as the data
is rolling in and we’re sitting and
we’re working on something boring and
technical like Bluetooth connection
strength something like that we more or
less accidentally plot a five-minute
snapshot of all the people hanging out
in the real world
this humble picture and this is
basically just all the people that are
hanging out between noon and 5 minutes
past noon on some Tuesday but when we
saw this picture we looked at each other
and we realized that something
significant had just happened and
immediately we jumped up started drawing
on the whiteboard and trying to sort of
figure out what this would mean and by
the way you know jumping up and drawing
on the whiteboard that is the nerd
so let me try and give you a sense of
why this is amazing why that five-minute
time window was the key and so the
reason is that if you take all the
connections over a full day you don’t
get something simple you get this
undecipherable green hair ball shown
here all right so the the the blue
Network takes advantage through this
super detailed data that we had
collected but no one had ever seen what
five minutes of a social system looks
like or even thought about what it would
look like and let me also emphasize this
point the green network that’s real data
and it’s for the same people and it’s
what researchers had looked up up until
then and that’s why the patterns that my
team and I had found were invisible to
them so because we were observing the
network the system for the right amount
of time that five-minute time window the
network fell into bits and pieces and
each little piece was a group of people
hanging out so simply by collecting
better data we had solved this
fundamental problem of finding groups
in social networks which is something
researchers around the world are working
on as we speak okay and that was just
the beginning because we could now
compare each five-minute window to the
one right next to it so noon to five
past five past to ten past and so on and
that means that we could study the
patterns of how groups form and to solve
over time but if people are truly
friends they don’t just meet once they
meet again and again over days and weeks
and months and we can think of a group
that meets again and again has a kind of
social context for the people in that
group right so the group could be our
study group soccer team drinking buddies
or something else entirely and now we
began to wonder well how do people jump
from group to group over time and
remarkably this idea of measuring how
people transition from social context to
social context it gives us a whole new
way of thinking about how people move
through the social space we don’t need
the whole network just the context and
technically behind the scenes that also
meant that we didn’t need the whole
complicated Network and we could write
down the relatively simple equations of
moving from social context to social
context and because the math was simpler
we had much better conditions for
understanding important real world
processes like the spread of epidemics
the spread of information and how
opinion spread that was exactly the type
of reefs of insights that I had hope for
when we started the project a
breakthrough and how we think about
social networks and one that could only
happen because we were able to zoom out
and observe
the entire anthill so it’s difficult for
me to even describe how relieved I was
when we were sitting on a fantastic
insight an insight that would give other
people other researchers across many
fields of science access to a new mental
toolbox a new way of thinking about
problems within their own fields and
that sense of relief set us free to be
even more creative because there had
recently been a very very cool paper
that showed how you collect people’s
future interactions based on where they
had been in the past and because we were
thinking about contexts and not networks
we realized that there’s this deep
similarity between how we move through
social space and how we move through
geographical space just like we moved
from place to place in geographical
space we move from context to context in
social space and because the problems
are essentially the same that means that
we could take these methods of location
prediction and transfer them directly to
our social data so now we had built a
machine that could predict people’s
future encounters so I thought it was
and believe it or not there’s one last
wrinkle to my story and so that is that
you have to remember that we also had
the data about how people move from
place to place so that means that we
could calculate both kinds of
predictability okay and we first showed
that people’s social life is about as
predictable as their movements but what
we found when comparing this social
predictability to our spatial
predictability was a kind of delicate
balance so in general people tend to go
to the same places and meet with the
same people in some weekly pattern but
one important exception is clear from
the data and that is that sometimes
humans go exploring we go out to see new
places and our movements become
unpredictable and our research shows
that precisely when our movements are
unpredictable that’s when our social
life is most predictable and I think
that the explanation is that when we
challenge ourselves to do new things we
tend to do that with the same people so
if I go hiking in some dangerous
mountainous terrain
I don’t bring some random stranger with
me I go with my friends right and so I
thought about it and I think almost all
of you in the audience are out exploring
today by being here you’re doing
something unusual and that means that
according to my theory you should be
here with someone you know pretty well
so so let’s put it to the test if you’re
here with someone you know pretty well
like your partner family member close
friend
please raise your hand ah pretty good
and now we should also test the opposite
perspective so please raise your hand if
you’re here on a first date I think that
so so I don’t know if we proved or
disproved my theory but for sure we do
have another data point we have a new anthill thank you
imagine seeing a university campus from
a helicopter but with detailed data
about every single individual so how
they move around who they’re hanging out
with and also all the online
communication mapped out that’s what you
need to really understand human social
networks now as a young researcher I
worked at US universities like Harvard
and Northeastern crunching data about
phone calls and we were trying to find
out how to analyze the network of all
the phone calls made by an entire nation
alright so that’s millions of
individuals and it’s billions of phone
calls but those billions of phone calls
they weren’t enough for me and the
reason is that I’ve become obsessed with
creating the best data set about
networks in the world I had this idea
that we could take our understanding of
social networks to the next level if we
could just zoom out and collect data
about an entire social system I imagined
this social system as a kind of massive
anthill teeming with activity you see
the thing is that as wonderful as it
sounds with all those billions of phone
calls they don’t say much about how
humans really connect to one another
only a fraction of our communication
happens over the phone so to make this
obsession of mine a reality I found this
group of individuals with lots of social
activity between them all the freshmen
at my university the Technical
University of Denmark
I got started on mapping out all their
communication and all their networks and
to do that I went out and I purchased
1,000 identical top-of-the-line
smartphones and we installed custom
software on each one to measure the
networks and as in the side that is a
lot of phones to install custom software
on of course these phones that I gave to
the students they would give me
information about the phone calls and
the text messages but the smart phone
also knows who you’re hanging out with
what’s going on in your Facebook feed
and much more and as another side can I
tell you something at this point I
wasn’t sleeping very well and the thing
that was keeping me awake was the weight
the sheer responsibility of this huge
machine that we were building to observe
this human anthill ok the budget was
tens of millions
I put an entire team of people to work
countless hours of effort and
collaborators depending on me and
frankly I had no idea what I was doing
because how could I no one had ever done
anything like this on a scale like this
before and the most scary thing was that
I had to come up with some kind of
fantastic scientific insight and in
research the result is the only novel if
you don’t know what it is ahead of time
so I was seriously worried that I made
too big a gamble so one day as the data
is rolling in and we’re sitting and
we’re working on something boring and
technical like Bluetooth connection
strength something like that we more or
less accidentally plot a five-minute
snapshot of all the people hanging out
in the real world
this humble picture and this is
basically just all the people that are
hanging out between noon and 5 minutes
past noon on some Tuesday but when we
saw this picture we looked at each other
and we realized that something
significant had just happened and
immediately we jumped up started drawing
on the whiteboard and trying to sort of
figure out what this would mean and by
the way you know jumping up and drawing
on the whiteboard that is the nerd
so let me try and give you a sense of
why this is amazing why that five-minute
time window was the key and so the
reason is that if you take all the
connections over a full day you don’t
get something simple you get this
undecipherable green hair ball shown
here all right so the the the blue
Network takes advantage through this
super detailed data that we had
collected but no one had ever seen what
five minutes of a social system looks
like or even thought about what it would
look like and let me also emphasize this
point the green network that’s real data
and it’s for the same people and it’s
what researchers had looked up up until
then and that’s why the patterns that my
team and I had found were invisible to
them so because we were observing the
network the system for the right amount
of time that five-minute time window the
network fell into bits and pieces and
each little piece was a group of people
hanging out so simply by collecting
better data we had solved this
fundamental problem of finding groups
in social networks which is something
researchers around the world are working
on as we speak okay and that was just
the beginning because we could now
compare each five-minute window to the
one right next to it so noon to five
past five past to ten past and so on and
that means that we could study the
patterns of how groups form and to solve
over time but if people are truly
friends they don’t just meet once they
meet again and again over days and weeks
and months and we can think of a group
that meets again and again has a kind of
social context for the people in that
group right so the group could be our
study group soccer team drinking buddies
or something else entirely and now we
began to wonder well how do people jump
from group to group over time and
remarkably this idea of measuring how
people transition from social context to
social context it gives us a whole new
way of thinking about how people move
through the social space we don’t need
the whole network just the context and
technically behind the scenes that also
meant that we didn’t need the whole
complicated Network and we could write
down the relatively simple equations of
moving from social context to social
context and because the math was simpler
we had much better conditions for
understanding important real world
processes like the spread of epidemics
the spread of information and how
opinion spread that was exactly the type
of reefs of insights that I had hope for
when we started the project a
breakthrough and how we think about
social networks and one that could only
happen because we were able to zoom out
and observe
the entire anthill so it’s difficult for
me to even describe how relieved I was
when we were sitting on a fantastic
insight an insight that would give other
people other researchers across many
fields of science access to a new mental
toolbox a new way of thinking about
problems within their own fields and
that sense of relief set us free to be
even more creative because there had
recently been a very very cool paper
that showed how you collect people’s
future interactions based on where they
had been in the past and because we were
thinking about contexts and not networks
we realized that there’s this deep
similarity between how we move through
social space and how we move through
geographical space just like we moved
from place to place in geographical
space we move from context to context in
social space and because the problems
are essentially the same that means that
we could take these methods of location
prediction and transfer them directly to
our social data so now we had built a
machine that could predict people’s
future encounters so I thought it was
and believe it or not there’s one last
wrinkle to my story and so that is that
you have to remember that we also had
the data about how people move from
place to place so that means that we
could calculate both kinds of
predictability okay and we first showed
that people’s social life is about as
predictable as their movements but what
we found when comparing this social
predictability to our spatial
predictability was a kind of delicate
balance so in general people tend to go
to the same places and meet with the
same people in some weekly pattern but
one important exception is clear from
the data and that is that sometimes
humans go exploring we go out to see new
places and our movements become
unpredictable and our research shows
that precisely when our movements are
unpredictable that’s when our social
life is most predictable and I think
that the explanation is that when we
challenge ourselves to do new things we
tend to do that with the same people so
if I go hiking in some dangerous
mountainous terrain
I don’t bring some random stranger with
me I go with my friends right and so I
thought about it and I think almost all
of you in the audience are out exploring
today by being here you’re doing
something unusual and that means that
according to my theory you should be
here with someone you know pretty well
so so let’s put it to the test if you’re
here with someone you know pretty well
like your partner family member close
friend
please raise your hand ah pretty good
and now we should also test the opposite
perspective so please raise your hand if
you’re here on a first date I think that
so so I don’t know if we proved or
disproved my theory but for sure we do
have another data point we have a new anthill thank you
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