Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)

Jukka-Pekka Onnela

Harvard University

Big Data for Development

United Nations Headquarters, New York City

July 10, 2012

Big Data, Social Networks, and Human Behavior

1Tuesday, July 10, 2012

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


http://www.boston.com/bigpicture/2008/08/the_large_hadron_collider.html


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/




• 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)

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



• 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)



http://desktopwallpaperdownload.files.wordpress.com/2012/02/network-space-lights-planets-high-wallpapers-full-hd.jpg




• 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)



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


Tie strengths in social networks

The weak ties hypothesis

Mark Granovetter, The strength of weak ties, American Journal of Sociology 78, 1360, 1973



Revisiting the hypothesis with aggregated cell phone data

• Tie strength

• Fraction of friends in common

Onnela, Saramäki, Hyvönen, Szabó, Lazer, Kaski, Kertész, BarabásiStructure and tie strengths in mobile communication networks, PNAS 104, 7332, 2007

15 min (3 calls)5 min

7 min

3 min



Onnela, Saramäki, Hyvönen, Szabó, Lazer, Kaski, Kertész, BarabásiStructure and tie strengths in mobile communication networks, PNAS 104, 7332, 2007


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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

Pulse of the nation: Mood from Twitter


Thank you

jponnela.com


Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)

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