Aaron Clauset is an assistant professor of听听and member of the听听at CU-麻豆影院. He recently accepted听听in Network Science, which is an international prize awarded annually to a researcher under 40 who has made fundamental contributions to the advancement of network science. Network science is an interdisciplinary field dedicated to understanding the structure and function of networks in all domains, from social networks to biological networks to technological networks. We talked to Clauset about how he uses network science in his research:
How did you become interested in network science?
I began studying networks during my doctoral work at the University of New Mexico. Although interest in networks stretches back to at least the early part of the 20th听century in sociology, network science as a modern interdisciplinary field was born only recently, as a result of the computer revolution. These technologies now allow scientists to record and study immense volumes of data on interactions in nearly every scientific field, from the way people interact with each other either online or offline, to how genes regulate each other or how food webs are structured, to how the structure of a network shapes how information flows across it. A long-running theme in my research, which started during my doctoral work, is the development of advanced algorithms that can identify subtle organizational patterns in networks, and use these patterns to make predictions.
What do you hope to do with your discoveries in network science?
Increasingly, networks are a powerful tool for making discoveries about the structure and function of complex systems in scientific domains, for example, in the social or biological sciences. Part of my research focuses on using network techniques to answer specific scientific questions. But I鈥檓 also hope to identify the basic organizing principles of networks that span different scientific domains. Insights from studying networks in one domain, such as human social networks, can often help us to better understand some aspects of networks in other domains, such as molecular interaction networks, or to develop more powerful tools for analyzing them.
Studying network science is allowing you to look at a broad range of subjects: faculty hiring, sports scoring, social networks like Facebook, and malaria virulence genetics. What have you discovered by researching the networks of so many things?
It鈥檚 definitely true that my research on networks has taken me across a pretty wide variety of topics. But they are all interesting! What I鈥檝e found is that there are surprising and evocative commonalities across many different systems, if one looks carefully. It鈥檚 exciting to discover these, and to think about how their appearance across different systems may point to more simple processes that underlay the observable complexity in the world.
What are the ingredients of a good network scientist?
It鈥檚 difficult to be a good network scientist today without being a good statistician and a good computer scientist. Network data is inherently more messy and difficult to understand than traditional types of data. So, making progress, either in developing new algorithms for analyzing the data or in applying network techniques to test scientific hypotheses, requires some technical skill. But, I also think it helps to have a good imagination and a healthy sense of skepticism. Networks are highly non-intuitive objects. Imagination can help you identify new ideas about how they behave, and skepticism will keep you keep from falling in love with your theories.
Do you tend to apply network science to other areas of your life? And how has it enriched your life?
Networks have shaped how I think about many things. For instance, I think about the spread of information differently now. Personal privacy is basically a network effect, and that places pretty strong limits on what any individual can do to maintain it. Knowing this has probably led me to be a bit more circumspect about posting information online. But more broadly, networks are everywhere in life, and I think taking a 鈥渘etwork perspective鈥� can help shed new light and new understanding on a many things, both mundane and not.
You can follow Clauset on Twitter @aaronclauset.听