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SOCNET  February 2009

SOCNET February 2009

Subject:

Cambridge Colloquium on Complexity and Social Networks

From:

david lazer <[log in to unmask]>

Reply-To:

david lazer <[log in to unmask]>

Date:

Wed, 25 Feb 2009 15:02:12 -0500

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text/plain

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*****  To join INSNA, visit http://www.insna.org  *****

I am pleased to announce our Spring, 2009 schedule for the Cambridge
Colloquium on Complexity and Social Networks.  Below is the schedule, plus
more detailed information for the first presentation.  If you are in town,
please feel free to drop in.  And also, please feel free to forward, and if
you would like to be added to the e-mail list, please e-mail
[log in to unmask]

David Lazer


*Cambridge** Colloquium on Complexity and Social Networks (Spring 2009)*

 Tanzeem Choudhury (Dartmouth), Using Sensors to Make Sense of People:
Inferring the Micro and Macro Level Properties of Social Networks from
Mobile Sensor Data
March 2, Taubman 275

Damon Centola (MIT), "Diffusion in Social Networks:  New Theory and
Experiments"
April 6, Taubman 275

Jennifer Chayes (Microsoft Research), TBD
April 13, Bell Hall (Belfer Building)



James Fowler (UCSD), Genes and Social Networks

April 27, Bell Hall (Belfer Building)



Eszter Hargittai (Northwestern), TBD
May 11, Bell Hall (Belfer Building)


-------------

Using Sensors to Make Sense of People: Inferring the Micro and Macro Level
Properties of Social Networks from Mobile Sensor Data

Abstract:
Human behavior in the real world is a difficult thing to study: it is not
possible to have human observers follow someone around all day, and surveys
often tend to biased and unreliable. On the other hand, sensor data is easy
to collect but inferring human behavior from this data is still a
challenging problem. In this talk, I will present the probabilistic
framework we have developed for inferring the micro-level dynamics of human
interactions as well as the macro-level social network structure from local,
noisy sensor observations. By studying the micro and macro levels
simultaneously we are able to explore the relationship between interaction
dynamics (local behavior) and network prominence (a global property), and
can identify the behavioral correlates of tie strengths within a network. We
believe these methods have the potential to allow more quantitative inquiry
into human behavior and social dynamics. They will also enable us to develop
socially aware ubiquitous computing systems that are cognizant of and
responsive to users' engagement with their social environment.

Bio:
Tanzeem Choudhury is an assistant professor in the computer science
department at Dartmouth. She joined Dartmouth in 2008 after four years at
Intel Research Seattle. She received her PhD from the Media Laboratory at
MIT. Her research involves developing machine-learning techniques for
systems that can reason about human activities, interactions, and social
networks in everyday environments. Tanzeem's doctoral thesis demonstrated
for the first time the feasibility of using wearable sensors to capture and
model social networks automatically, on the basis of face-to-face
conversations. She was recognized in MIT Technology Review's 2008 TR35 list
for her work in this area.


-- 
David Lazer (www.davidlazer.com)
Director, Program on Networked Governance
Associate Professor of Public Policy
Harvard Kennedy School
Harvard University
The netgov blog: http://www.iq.harvard.edu/blog/netgov/

_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
network researchers (http://www.insna.org). To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.

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