The vast power of the Internet is undergoing probing analysis within the Social Cognitive Networks Academic Research Center. Boleslaw Szymanski, the center’s director, focuses his research on the fundamentals of social and cognitive network science. “Today’s computer technology is both the enabler of new social interactions and the tool for observing and measuring them,” said Professor Szymanski. “These interactions make societies more diverse and more dynamic and they increase the global impact of small, focused groups, creating both new opportunities and new dangers.”
The center brings together researchers from varied fields, including the social sciences, neuroscience, cognitive science, medicine, computer science, mathematics, and engineering, developing mathematical formulas and models to gauge the effects of social cognitive networks. Matthew Kirby ’13, a physics major, who was part of an interdisciplinary research team during his sophomore and junior years, found the work fascinating. “We were looking at opinions and how they evolve over time, seeing how some people will only be influencers, while others can’t be influenced,” said Kirby.
“ We are in an entirely new world where Twitter, cellphones, and wireless communication change the way we interact with each other.”- Boleslaw Szymanski
Sibel Adali, Associate Professor of Computer Science, is studying how trust can be measured. “Now that everyone is using computers, we can look at how they can be used to help people—to make the right recommendations, for instance,” said Professor Adali. “To be able to do this, you have to understand how people really trust. There is the psychological component and the cognitive.”
Priti Kumar, a senior majoring in computer science, has been researching this issue with Professor Adali. “In today’s society, we see a lot of social networking and are placing a lot of trust in people we can’t see, whether it’s on Amazon or Epinions or wherever,” said Kumar. “I am looking at how trust can be propagated through a network—how it moves along a line—and how that can lead us to create better models of systems that can actually work.”