Nathan Eagle's presentation at eComm 2008

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Information about Nathan Eagle's presentation at eComm 2008

Published on April 9, 2008

Author: eComm2008

Source: slideshare.net

Challenges for the Mobile Industry: Sensing, Scaling, and Sustaining Nathan Eagle Research Scientist / Postdoctoral Fellow / Fulbright Lecturer Massachusetts Institute of Technology / The Santa Fe Institute / U of Nairobi et al.

SENSING: Reality Mining Eagle, N. “Machine Perception and Learning of Complex Social Systems", PhD Thesis, Massachusetts Institute of Technology . 2005. 400,000 continuous hours…

400,000 continuous hours…

SCALING: Population Level Data Analysis Data: Social Network of a Nation 250 million nodes (phone #’s) 5,000 edges/second (calls) 12 billion calls/month Objectives Network Customer Value Optimize Direct Marketing Strategies Diffusion of Products and Churn Aggregate Behavior

Data: Social Network of a Nation

250 million nodes (phone #’s)

5,000 edges/second (calls)

12 billion calls/month

Objectives

Network Customer Value

Optimize Direct Marketing Strategies

Diffusion of Products and Churn

Aggregate Behavior

SUSTAINING: The Developing World Why Africa? Fastest growing 10,000’s CS graduates annually Underserved Mobile Software Market EPROM Education Research Entrepreneurship http://mit.edu/eprom

Why Africa?

Fastest growing

10,000’s CS graduates annually

Underserved Mobile Software Market

EPROM

Education

Research

Entrepreneurship

SMS Bloodbank Bloodbank Supply Chain (mis)Management Sambaza – Airtime Sharing 250 lines of code National Deployment?

Bloodbank Supply Chain (mis)Management

Sambaza – Airtime Sharing

250 lines of code

National Deployment?

MoSoko: Craig’s List without Computers Legacy Handsets Flashing SMS Labor Bulletin Boards Community Service Delivery Web SMS Voice (Asterisk)

Legacy Handsets

Flashing

SMS Labor

Bulletin Boards

Community Service Delivery

Web

SMS

Voice (Asterisk)

Talk Takeaways: SENSING Individual Behavior Prediction Relationship Inference Organizational Rhythms Scale-up to 100k http://reality.media.mit.edu

Individual Behavior Prediction

Relationship Inference

Organizational Rhythms

Scale-up to 100k

Talk Takeaways: SCALING Large-Scale Networks Aggregate Behavior Diffusion Scaling Laws http://mit.edu/networks http://santefe.edu

Large-Scale Networks

Aggregate Behavior

Diffusion

Scaling Laws

Talk Takeaways: SUSTAINING Legacy Handsets Mobile Web Bypass Entrepreneurship Research Education http://eprom.mit.edu

Legacy Handsets

Mobile Web Bypass

Entrepreneurship

Research

Education

Questions? Nathan Eagle [email_address]

Nathan Eagle

[email_address]

EPROM: Education Python for Rapid Prototyping SMS Bootcamp Mobile Phone Programming for Entrepreneurs

Python for Rapid Prototyping

SMS Bootcamp

Mobile Phone Programming for Entrepreneurs

Conversation Modeling Conversation Finite State Machine Variable-duration (semi-Markov) HMMs [Mu02] J N S The Influence Model with Hidden States [BCC01] Sumit Basu, Tanzeem Choudhury, Brian Clarkson and Alex Pentland. Learning Human Interactions with the Influence Model. MIT Media Lab Vision and Modeling TR#539, June 2001. Kevin Murphy. Modeling Sequential Data using Graphical Models. Working Paper, MIT AI Lab, 2002

Prosody Analysis Speaking Time: Circle size Transition Probability: Width of the link Average Interest Level: Circle color (individual) Circle border (group) Nathan Eagle and Alex Pentland, “Social Network Computing”, Ubicomp 2003: Ubiquitous Computing, Springer-Verlag Lecture Notes in Computer Science 2864 , pp. 289-296, 2003.

Speaking Time:

Circle size

Transition Probability:

Width of the link

Average Interest Level:

Circle color (individual)

Circle border (group)

An eComm 2008 presentation – http://eCommMedia.com for more

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