Spoken Networks
The Spoken Networks projects studies how real-world, face-to-face social behavior can be measured and modeled in ways that simultaneously protect privacy and provide new insight into the dynamics of human social behavior.
Publications
- Discovering Long Range Properties of Social Networks with Multi-Valued Time-Inhomogeneous Models (2010)
- Dynamic Multi-Valued Network Models for Predicting Face-to-Face Conversations (2009)
- Collective Modeling of Human Social Behavior (2009)
- Towards the Automated Social Analysis of Situated Speech Data (2008)
- Learning Hidden Curved Exponential Random Graph Models to Infer Face-to-Face Interaction Networks from Situated Speech Data (2008)
- Creating Social Network Models from Sensor Data (2007)
- Conversation Detection and Speaker Segmentation in Privacy-Sensitive Situated Speech Data (2007)
- Capturing Spontaneous Conversation and Social Dynamics: A Privacy Sensitive Data Collection Effort (2007)
- A Privacy-Sensitive Approach to Modeling Multi-Person Conversations (2007)
Research Groups
Last changed Fri, 2012-11-16 11:28

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