Reality Mining: Inference in Complex Social Systems via the Mobile Phone

Nathan Eagle (MIT)
General
Location: Marina Ballroom D

Nathan Eagle has used mobile phones to continuously gather information including proximity, location, and communication from 100 human subjects at MIT. Systematic measurements from these people over the course of nine months have generated one of the largest dataset of continuous human behavior ever collected, representing over 300,000 hours of daily activity. Additionally, in collaboration with one of Europe’s major telecommunication companies, Eagle is currently analyzing the call logs of an entire country—a dynamic social network consisting of 250 million nodes (people) and 12 billion temporal edges (calls).

In this talk, Eagle will describe how this type of data can be used to uncover the structure in behavior of both individuals and organizations, infer relationships, and study social network dynamics. By combining theoretical models with rich and systematic measurements, he shows it is possible to gain insight into the underlying behavior of complex social systems.

While results such as uncovering scaling laws from the communication patterns of hundreds of millions of people will certainly be one emphasis in this talk, of equal importance is how this data can enable applications that improve our society. Eagle will demonstrate a variety of ways these insights into our own behaviors can be used to develop applications that better support both the individual, organization, and society.

More information about these projects is available at http://reality.media.mit.edu.

Photo of Nathan Eagle

Nathan Eagle

MIT

Nathan Eagle is a Research Scientist at the MIT and Postdoctoral Fellow at the Santa Fe Institute. In 2007, Nathan taught mobile phone programing at the University of Nairobi as a Fulbright Lecturer. He holds a PhD from the Massachusetts Institute of Technology, and graduated from Stanford University with a B.S. in Mechanical Engineering, an M.S. in Management Science and Engineering, and an M.S. in Electrical Engineering.

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