“The study of networks helps to explain how a whole comes to be greater than the sum of its parts — whether that whole is an organism or a society or a telecommunication system.”
Yale Institute for Network Science (YINS)
- Co-Directors: Daniel A. Spielman, Dr. Nicholas A. Christakis
- Web Site: Human Nature Lab
“Since many vexing social problems affect us as a group, and not just as individuals, network science offers great promise for concretely addressing them. Amazing new capacities at the intersection of the computational, biological, and social sciences are enabling us to develop startling new insights into individual and collective human behavior. YINS seeks to deploy this emerging area of study to its full potential: driving fresh discoveries, applying novel methods of analysis, and developing more effective approaches to interventions.” -Nicholas Christakis
“We believe that researchers will benefit greatly from better understanding the approaches taken in other disciplines. YINS will achieve synergy by gathering faculty who analyze networks with those who use networks to make predictions and those who attempt to design and control network processes. A goal of YINS is to expose researchers to the phenomena, measurements, methodologies, and challenges of those from different disciplines so that, through cross-fertilization, new techniques and methodologies can be developed.” -Daniel A. Spielman
The fields involved include engineering, computer science, the social sciences, biology, math. physics, and medicine.
Examples of network phenomena from many disciplines that faculty affiliated with YINS may study include:
• the design of power, communication, and sensor networks, as well as dynamically changing robotic networks
• the conduct of large-scale experiments with online and offline networks to facilitate the emergence of desirable properties, such as cooperation, innovation, voting, and health
• the impact of social networks on the diffusion of individual behaviors and forms of collective action
• the properties of communication and exchange within different networks that determine the outcomes of diverse markets
• algorithms for the analysis of networks
• systems biology and gene regulation networks, and their role in pathogenesis and drug discovery
• phase transitions in spin glasses and complex systems
• using online and offline networks to track communicable diseases
• epidemiology and the use of field trials in settings as diverse as American schools and developing world villages to enhance public health
While the fields that study network interactions create different abstractions and measure networks in different ways, they share common technical and scientific challenges, including the development of tools for processing big data; developing new models for complex networks; understanding how networks change; developing techniques for learning and inference in networks; developing methodologies for the design of networks; and understanding how local interactions can lead to emergent global behavior. The practical implications are wide-ranging.
Work in the lab focuses on exploring fundamental properties of human social networks. Some work involves the use of large-scale, online experiments, or field trials in the developing world. Other work examines the biological determinants and consequences of social network interactions, with a particular emphasis on the genetic and evolutionary origins and implications of human network interactions.