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Predicting the Behavior of Techno-Social Systems

Predicting the Behavior of Techno-Social Systems. Alessandro Vespignani Science, Vol. 325 24 July 2009 (Prepared by Hasan T Karaoglu). Outline. What is the Question? Possible Answers Reality Mining (and Proxy Networks) Network Thinking Highlights Some Applications and Caveats

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Predicting the Behavior of Techno-Social Systems

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  1. Predicting the Behavior of Techno-Social Systems Alessandro Vespignani Science, Vol. 325 24 July 2009 (Prepared by Hasan T Karaoglu)

  2. Outline • What is the Question? • Possible Answers • Reality Mining (and Proxy Networks) • Network Thinking • Highlights • Some Applications and Caveats • Additional Slides • Couple of Examples • Progress Report

  3. What is the Question? • Techno-social systems • Large-scale physical infrastructure (Power Grids, Transportation Systems, Internet ...) • Embedded in Dense Web of Communication • Led by Human • While we can predict weather conditions successfully, why we couldn’t achieve same success in predicting social systems’ behavior?

  4. What is the Question? • Quantitative Prediction of Spatio-Temporal Patterns of Pandemics? • Effects of connecting billions of people from China and India using Internet? • Internet Stability and Growth?

  5. Possible Answers • To predict: • Real world patterns discovered in data • Forming models based on patterns • Not Enough Data • Centuries of Weather Condition Records • Not enough data for social systems till lately • Mobility, Adaption of Certain Behavior, Risk Perception • Fundamentals of System Model • Physical Laws governing fluids and gases • We need better understanding of social interaction

  6. Reality Mining • Level of Information Flow • Not only due to Computational Power • Involvement of machines into our life • Machine Sensed Data Related to Our Lives • Human Mobility • http://en.eurobilltracker.com and www.wheresgeorge.com • Cell Phones, PDAs, Bluetooth, WiFi, GPS, Sensors • Mobile Phone Track of 100K people over 6 months.

  7. Reality Mining

  8. Reality Mining Airline Traffic

  9. Reality Mining Commuting Traffic

  10. Reality Mining • What it brings? • Dynamics of Epidemics • Evolution of Languages and Dialects • Bio-invasion • Foraging for Information

  11. Network Thinking • Real World Networks are mostly “self-organized” • Heavy Tailed and Skewed • Heterogenity • Similar Behavior in Different Granularities • Complexity of Techno-social Systems • “Network Mindset” • Ex: • 14th Century Plague Epidemic : Spatial Diffusion • SARS : Commercial Air Travel

  12. Network Thinking

  13. Highlights • Large Scale Systems: • Don’t exhibit engineered or planned behavior • Ex: Commuting Networks • Final System behavior is result of: • Dynamics of all scales • Events take place at different timelines • Bottom-up Approach • Behaviors of Individuals shape the Large-Scale System Behavior • Flocks of Birds, Internet Topology

  14. Highlights (Bottom-up Approach) • Flocking • Separation (don’t crowd your neighbors) • Alignment (position yourself in the middle) • Cohesion (follow your neighbors) • Internet Topology • Wealth Based Topology Generator • Establish links as you have money • Go bankrupt when you broke • Randomly choose whom to connect • Maxwell-Boltzman Distribution

  15. Highlights • Social Atoms to Social Aggregate • The shift from the study of a small number of elements to the study of the behavior of large-scale aggregates is equivalent to the shift from atomic and molecular physics to the physics of matter.

  16. Some Applications and Caveats • System Modeling • TRANSIM, EPISIM • Counter-Intuitive Ideas • Avoiding Cascading Failure • Preventing Further Damage, Ex: Wild Fire, Immunization • Limits • Steady State Behavior (Catastrophe ?) • Social Adaptive Behavior (Self fulfilling Prophecy) • Ethical Issues?

  17. Progress Report • Total Disappointment: Twitter • Reddit, Diggit • Spinn3r? • Emotion Extraction?

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