Call for Papers

The study of human behavior has always intrigued social scientists interested in enhancing effectiveness and individual well-being in social systems. By using sensors (cameras, microphones, accelerometers, etc.) that provide objective, quantitative measurements of social behavior, we now can automatically measure individual and collective patterns of behavior; predict human behavior from unconscious social signals; identify social affinity among individuals; and enhance social interactions by providing real-time feedback.

 

We are looking forward to your submission and participation in the workshop. Following are the key areas of interest.

- Sensors for social computing

- Group behavior modeling using sensors

- Social systems simulations

- Organizational engineering

- Social analysis methods based on sensor data

- Feedback systems based on real-time sensor data

 

 

Workshop organizers:

Taemie Kim, Daniel Olguin Olguin, Ben Waber (MIT Media Lab)

Oliver Brdiczka (PARC)

Miki Hayakawa (Hitachi Central Research Laboratory)

 

 

Paper selection process:

Authors are invited to submit original, unpublished research papers that are not being considered in another forum. Manuscripts can be between 4 to 8 (IEEE style) pages. Please follow the IEEE conference paper format prepare your papers with 8.5'' x 11'', two-column format. Submission should include the title, author(s), affiliation(s), e-mail address(es), tel/fax numbers, abstract, and postal address(es) on the first page.

 

Please submit your manuscript to:

socialCom09@media.mit.edu by May 22, 2009 (extended deadline)

 

Submitted papers will be evaluated by their relevance to the topic, novelty and scientific contribution. Once a paper has been accepted, at least one author is required to attend the conference and present the paper. Electronic submission of manuscripts (in PDF format) is required. Accepted papers will be published in the main conference proceedings of SocialComp-09.

 

Workshop on

Sensor-Based Models and Feedback Systems

                                              for Social Computing