Research scientist Nathan Eagle kicks off a new lecture series with a talk on collective intelligence-gathering.
Networks are everywhere. From computers on the Internet to infected patients in an epidemic to molecular processes within a cell, complex webs of interactions between many different entities play critical roles in both society and the natural world. Such networks are at the heart of an increasing number of research efforts at Penn State and elsewhere. In light of the growing importance of this emerging field, the Office of the Senior Vice President for Research is sponsoring a Distinguished Lecture Series on Network Science and Research.
In the first of these lectures, Nathan Eagle, a research scientist at the Massachusetts Institute of Technology and a postdoctoral fellow at the Santa Fe Institute, spoke about his work applying machine learning and network analysis techniques to large human behavioral datasets generated by mobile phones.
View the handout from his talk on Inference in Complex Social Systems (PDF)
Eagle has used mobile phones to continuously gather information including proximity, location, and communication from human subjects. Systematic measurements from these people over the course of nine months has generated one of the largest datasets of continuous human behavior ever collected, representing over 300,000 hours of daily activity. Additionally, in collaboration with several European and African telecommunication companies, he is currently analyzing the call logs of entire countries—dynamic social networks consisting of up to 250 million nodes and 12 billion temporal edges. In his talk he describes 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.
Eagle's talk took place on campus on November 5. For the rest of the series schedule, please check