Tanzeem Choudhury © 2002

SHORTCUTS: CREATING SMALL WORLDS

Principal Investigators: Tanzeem Choudhury and Alex Pentland                   

The first successful experiment in automatically learning the communication patterns

 within a community and the interaction dynamics using wearable sensing devices

 

      

The  "Sociometer"

              

                                            

Publications:

 

Sensing and Modeling Human Networks

Tanzeem Choudhury

MIT PhD Thesis

August 2003

 Modeling Face-to-Face Communication using the Sociometer, 
Choudhury, T., and Pentland, A
To Appear in: Proceedings of the International Conference on Ubiquitous Computing, Seattle, WA. October 2003 


Sensing and Modeling Human Networks using the Sociometer, Choudhury, T., and Pentland, A
To Appear in: Proceedings of the International Conference on Wearable Computing, White Plains, NY. October 2003 


Learning Communities: Connectivity and Dynamics of Interacting Agents, Choudhury, T., Clarkson, B., Basu, S., and Pentland, A. To appear in the Proceedings of the International Joint Conference on Neural Networks - Special Session on on Autonomous Mental Development. July 2003. 


The Sociometer: A Wearable Device for Understanding Human Networks, Choudhury, T. and Pentland, A. (November 2002) MIT Media Lab TR# 554. Presented at the Conference on Computer Supported Cooperative Work (CSCW '02) (Workshop: Ad hoc Communications and Collaboration in Ubiquitous Computing Environments) 

In the Shortcuts project, we are developing methods to automatically and unobtrusively learn the social network structure that arises within a group based on data collected using the sociometer. The questions we are exploring are:
-  Who are the key players in the community? 
-  What are the dynamics of people's interactions and how individual influence each other's   

   dynamics?

-  How does information diffuse within the community?

 

The Experiment:

-  A group of  23 people within a community agree to wear sociometers - 6 hours daily.
-  We collect information about their interactions over  an extended period of time (2weeks).
-  Learn group structure and dynamics using statistical  pattern recognition techniques.
-  Learn how interaction dynamics influence the social network relationships

Experimental Details:

The users agree to have the device on them for the duration that they are on MIT campus. We collected the following data from each individual  -

-  his/her neighborhood information, i.e. the people nearby using IR tags 
-  speech features - spectral features, speech energy, duration, and pitch (using onboard  

   microphone)  
-  motion information (using two 2-axis accelerometer).

 

We have collected 1518 hours of interaction data from 23 individuals over two-weeks.

Hardware Details:

We use the hoarder board with the multi-sensor board extension for data collection in this project. The hoarder board is a microcontroller-based data acquisition platform suitable for user sensing applications. Developed by Vadim Gerasimov, Rich Devaul and Josh Weaver, the general-purpose hoarder board is customized for particular applications through specially designed daughter boards, which provide the sensing hardware.

Design:

Special thanks to Brian Clarkson for the effort he put into the design of the shoulder mount.

COUHES:

The use of human subjects for this project has been approved by COUHES (application # 2889)