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Big Data, Social Networks, and Human Behavior
Jukka-Pekka Onnela
Harvard University
Big Data for Development
United Nations Headquarters, New York City
July 10, 2012
Tuesday, July 10, 2012 1
Overview
• Progress in science has always been driven by data
• Explosion in the amount and type of data
• “Big data” refers to large and complex data sets
• Often multidimensional, longitudinal, digitally generated
• The big data phenomenon has its origin in Moore’s law:
• The number of transistors on integrated circuits doubles every 18 months
• Sensors are cheaper, smaller, everywhere
• Enhanced computational capacity
http://en.wikipedia.org/wiki/Moore%27s_law
Tuesday, July 10, 2012 2
http://www.boston.com/bigpicture/2008/08/the_large_hadron_collider.html
Tuesday, July 10, 2012 3
Large Hadron Collider (LCH)
• Large Hadron Collider (LHC) at CERN is the biggest machine ever built
• Largest underground ring has a circumference of 27 kilometers (17 miles)
• 1232 dipole magnets, each 15 meters long weighing 30 tons
• Vacuum is 10 trillionth of an atmosphere
• Experiments generate 100MB of data (particle trajectories) each second
• Higgs boson
http://www.runfam.com/2011/10/why-the-hare-may-never-beat-the-tortoise-zenos-paradox-the-paradox-of-motion/
Tuesday, July 10, 2012 4
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Networks and mobile sensing
• Mobile phones have been used in the past few years to study the structure
of human social and communication networks
• Networks consist of nodes (actors) and ties (interactions)
• The field of research that studies networks, their structure and function, is
called network science (in physics and mathematics) or social network
analysis (in sociology and statistics)
Tuesday, July 10, 2012 6
Networks and mobile sensing
• Network theory, when applied to social networks, has a simple premise
• People are connected, therefore our health is connected
• People are connected, therefore our economic wellbeing is connected
• Mobile phones have enormous potential for the study of human social networks
and human behavior “in vivo,” in a natural context outside laboratories
• Social behavior has remained essentially unchanged for millennia, but now, for
the first time, we have the opportunity to study it at large scale
Tuesday, July 10, 2012 7
Networks and mobile sensing
• Besides communication, smartphones have sensors and computing capabilities
• These possibilities have led to a new research field called mobile phone sensing
• Mobile sensing has evolved in the past few years for several reasons
(1) Availability of cheap embedded sensors
• Gyroscope, compass, accelerometer, proximity sensor, ambient light
sensor, two cameras, microphone, GPS, WiFi, Bluetooth
(2) Smartphones are programmable
(3) Software can be easily distributed
(4) Significant computational power (phone & cloud)
• Each phone can generate 1kB of data / second (conservative)
Tuesday, July 10, 2012 8
http://desktopwallpaperdownload.files.wordpress.com/2012/02/network-space-lights-planets-high-wallpapers-full-hd.jpg
Tuesday, July 10, 2012 9
Networks and mobile sensing
• Expect 6 billion phone subscriptions by the end of 2012
• This results in 6 million MB / second, or 6 TB / second, of data
• This is 60,000 more data than CERN generates (conservative)
• Twofold opportunity:
• Use mobile phone sensing to learn about the individuals (nodes)
• Use mobile phone communication patterns and network theory to
learn about the structural connections between individuals (ties)
Tuesday, July 10, 2012 10
Phone calls and texts in a European network
• 20% market share
• 18 weeks (126 days)
• Private subscriptions
• N = 7M; L = 23M
Animation by Mikko Kivelä, Aalto University
Tuesday, July 10, 2012 11
Tie strengths in social networks
The weak ties hypothesis
Mark Granovetter, The strength of weak ties, American Journal of Sociology 78, 1360, 1973
Tuesday, July 10, 2012 12
Tie strengths in social networks
Revisiting the hypothesis with aggregated cell phone data
• Tie strength
• Fraction of friends in common
7 min
15 min (3 calls)
5 min
3 min
Onnela, Saramäki, Hyvönen, Szabó, Lazer, Kaski, Kertész, Barabási
Structure and tie strengths in mobile communication networks, PNAS 104, 7332, 2007
Tuesday, July 10, 2012 13
Tie strengths in social networks
Onnela, Saramäki, Hyvönen, Szabó, Lazer, Kaski, Kertész, Barabási
Structure and tie strengths in mobile communication networks, PNAS 104, 7332, 2007
Tuesday, July 10, 2012 14
Tie strengths in social networks
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Tie strengths in social networks
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Tie strengths in social networks
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Tie strengths in social networks
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Pulse of the nation: Mood from Twitter
Understanding the Demographics of Twitter Users; A Mislove, S Lehmann, YY Ahn, JP Onnela, JN Rosenquist;
Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, Barcelona, Spain, 2011
Tuesday, July 10, 2012 20
Thank you
jponnela.com
Tuesday, July 10, 2012 22
