Network Science

Northeastern’s Network Science research and core of internationally recognized researchers are central to the University’s leadership in the emerging field of network science. Members of the college’s Network Science, Artificial Intelligence, Human-Computer Interaction, and Network Security research groups are all addressing issues related to the structure of the Internet, the World Wide Web, and social and biological networks.

The Network Science research group incorporates the perspectives of computer science as well as other disciplines, such as political science and physics, to investigate important questions related to technology’s impact on social networks and how technology can enhance understanding of social and natural systems.

Group members are examining social networks and short paths to determine how individuals within these networks act as hubs. Using the “digital breadcrumbs” people leave behind when they use technology, researchers are analyzing the effects of social networks on politics and organizations, determining patterns that help in understanding human interactions during elections, collective creativity in teams, memes on the Internet, and the spread of disease. They are also exploring security issues related to social networks, including privacy and the consequences of potential disruptions and failures of interdependent networks.

Team Achievements

  • Awarded a National Science Foundation (NSF) grant to lead the first interdisciplinary study of the consequences of potential disruptions and failures of interdependent networks, such as the Internet and the power grid
  • Discovered scale-free networks and developed a model to explain their widespread emergence in social networks and other social, technological, and natural systems
  • Conducted a groundbreaking examination of the Internet’s impact on political views
  • Completed the first large-scale study of social network growth, identifying common underlying properties in the You Tube, Flickr, Live Journal, and Orkut networks
  • Received NSF grant support to develop systems, networks, and distribution systems that reflect emerging patterns of content sharing over the Internet, develop a means to limit users’ vulnerability to online fraud, and measure the prevalence of incorrect privacy settings on social network sites
  • Developed a system for China’s largest social network to detect fake accounts.