Doctoral Dissertation Research: Designing Collaboration Networks to Optimize Collective Problem Solving

本项目研究协作网络结构如何影响集体问题解决的成功。尽管直觉表明，支持信息有效扩散的网络作为一个整体表现得更好，但理论工作提出了网络效率与问题解决成功之间的负相关关系。换句话说，它假设效率较低的通信网络可能会促进更有效的问题解决，因为人们需要独立地寻找问题的解决方案。信息的多样性增加可能会增加工作组在达成共识之前找到更好解决方案的机会。由于规模和设计的限制，对这一理论进行实证评估的尝试一直没有定论。本研究利用观察和实验两种新的在线资源，研究了大型经验交流网络中网络效率对集体问题解决的影响。该项目对加强研究和教育领域的协作网络，以及设计科学和工业领域的高效团队结构具有重要意义。本项目将深入了解科学研究人员之间的协作网络结构如何影响创新的速度和质量。它将确定如何设计分布式在线协作网络，为政策制定者和行业管理人员提供改进群体和提高解决问题能力的新战略。

This project examines how the structure of collaboration networks affects the success of collective problem solving. Although intuition would suggest that networks which support the efficient diffusion of information perform better as a collectivity, theoretical work has proposed an inverse relationship between network efficiency and success in problem solving. In other words, it posits that less efficient communication networks may promote more effective problem solving because people need to search independently for solutions to problems. The increased diversity of the information might improve the chances that the group will find a better solution before arriving at a consensus. Attempts to evaluate this theory empirically have been inconclusive due to limitations of their scale and design. Using novel online resources, both observational and experimental, this research studies the effects of network efficiency on collective problem solving within large empirical communication networks. This project has implications for enhancing collaboration networks in research and education, and for designing efficient team structures in science and industry.This project will provide insight into how the structure of collaboration networks among scientific researchers can influence the rate and quality of innovation. It will identify the ways that distributed, online collaboration networks can be designed to provide policymakers and industry managers with new strategies for improving groups and for enhancing problem solving capacities.