In modern life, due to the increasing complexity of tasks and accuracy of labor division, the
situation that one problem can be solved by a single person has become history. Instead, problem resolution is the result of dynamic social collaboration of multiple experts toward a unified goal. With the emerge of Web 2.0, such collaborations are inter-disciplinary and global.
Understanding experts' skills and their interactions in a collaborative social network that drives problem-solving processes is the key to accelerate problem resolution and decision making. However, studies of collaborative innovation networks have been so far limited
to be qualitative, based on questionnaire and surveys, which are subjective, inaccurate and costly.
In this research, we are developing computational foundations and quantitative frameworks to model, optimize, and exploit collaborative social networks to expedite problem-solving and to enhance team organizations. Specifically, we address the following problems:
- Modeling Collaborative Social Networks from Problem Solving Processes
- Quantitatively Profiling Experts and Relations in the Network
- Optimizing Problem Solving Processes