Your SlideShare is downloading. ×
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Big Data, Social Networks & Human Behavior (Jukka-Pekka Onnela)
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

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

1,348

Published on

Presentation by Jukka-Pekka Onnela, Assistant Professor of Biostatistics at Harvard University's School of Public Health. Presented at roundtable on "BIg Data for Development" hosted by Global Pulse, …

Presentation by Jukka-Pekka Onnela, Assistant Professor of Biostatistics at Harvard University's School of Public Health. Presented at roundtable on "BIg Data for Development" hosted by Global Pulse, an innovation initiative of the United Nations (www.unglobalpulse.org).

Published in: Real Estate, Business, Technology
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
1,348
On Slideshare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
21
Comments
0
Likes
2
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Big Data, Social Networks, and Human Behavior Jukka-Pekka Onnela Harvard University Big Data for Development United Nations Headquarters, New York City July 10, 2012Tuesday, July 10, 2012 1
  • 2. 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_lawTuesday, July 10, 2012 2
  • 3. http://www.boston.com/bigpicture/2008/08/the_large_hadron_collider.htmlTuesday, July 10, 2012 3
  • 4. 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
  • 5. Tuesday, July 10, 2012 5
  • 6. 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
  • 7. 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 scaleTuesday, July 10, 2012 7
  • 8. 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
  • 9. http://desktopwallpaperdownload.files.wordpress.com/2012/02/network-space-lights-planets-high-wallpapers-full-hd.jpgTuesday, July 10, 2012 9
  • 10. 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
  • 11. 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 UniversityTuesday, July 10, 2012 11
  • 12. Tie strengths in social networks The weak ties hypothesis Mark Granovetter, The strength of weak ties, American Journal of Sociology 78, 1360, 1973Tuesday, July 10, 2012 12
  • 13. 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, 2007Tuesday, July 10, 2012 13
  • 14. Tie strengths in social networks Onnela, Saramäki, Hyvönen, Szabó, Lazer, Kaski, Kertész, Barabási Structure and tie strengths in mobile communication networks, PNAS 104, 7332, 2007Tuesday, July 10, 2012 14
  • 15. Tie strengths in social networks 15Tuesday, July 10, 2012 15
  • 16. Tie strengths in social networks 16Tuesday, July 10, 2012 16
  • 17. Tie strengths in social networks 17Tuesday, July 10, 2012 17
  • 18. Tie strengths in social networks 18Tuesday, July 10, 2012 18
  • 19. Tuesday, July 10, 2012 19
  • 20. 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, 2011Tuesday, July 10, 2012 20
  • 21. Thank you jponnela.comTuesday, July 10, 2012 22

×