Collaborative Research: Innovation in Social Networks

最近大规模网络和在线通信的增长产生了网络传播信息的新方式。但是许多研究问题仍然没有得到解答，比如网络如何影响创新，以及网络结构如何影响思想或技术之间的竞争。这项研究的目的是研究科研团体和它们之间的联系如何影响创新。它发展了一种理论，说明个人之间的联系和缺乏联系如何影响创新过程，特别关注跨越不同社区的“边界代理人”的作用。知识价值。该项目处于计算机科学和经济学的前沿。计算机科学家长期以来一直在研究信息是如何产生和处理的。长期以来，经济学家一直在研究创新的激励机制。这个项目引入了一个新的范例。它研究人员和企业网络中的创新，信息通过网络链接流动。发展这种范式需要对网络的图论特性和参与者的动机有深刻的理解。主要研究人员的组合工具不仅代表了计算机科学和经济学的重大方法进步，而且代表了更广泛的科学。更广泛的影响。该项目增加了妇女和代表性不足的群体对科学的参与。研究生课程训练学生使用所有相关领域的最先进的网络科学工具，包括经济学、社会科学、数学和计算机科学，而本科课程则包括社会网络实例。此外，该研究促进了对代表性不足的群体参与社会和经济网络的理解。最后，该项目的科学目标是发展知识，为决策者设计创新、发现和多样性的激励措施提供信息。

The recent growth in large-scale networks and online communication has generated new ways in which networks can diffuse information. But a number of research questions remain unanswered, such as how networks affect innovation and how network structure shapes competition among ideas or technologies.The goal of the research is to examine how research communities and links between them affect innovation. It develops a theory of how connections and absences of connections among individuals influence the process of innovation, with particular attention paid to the role of "boundary agents" who straddle different communities.Intellectual Merit. The project is poised at the frontier of computer science and economics. Computer scientists have long studied how information is created and processed. Economists have long studied incentives for innovation. This project introduces a new paradigm. It studies innovation in networks of people and firms, where information flows through network links. Developing this paradigm requires a deep understanding of the graph-theoretic properties of the network and the incentives of the participants. The combined tools of the principal investigators represent a significant methodological advance not only for computer science and economics, but the sciences more generally.Broader Impact. The project increases participation of women and under-represented groups in science. A graduate course trains students in state-of-the-art tools in network science from all relevant fields including economics, social sciences, mathematics, and computer science, while under graduate courses incorporate social network examples. In addition, the research advances understanding about the participation of underrepresented groups in social and economic networks. Finally, the scientific aims of the project develop knowledge that can inform policy makers in designing incentives for innovation, discovery, and diversity.