Using the graph algorithm to understand behavior in two worlds

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“We want to use graph algorithms to understand people’s behavior in two worlds. One is the online, virtual world and how people interact with each other on some social media platform; the other world is the physical world and how people engage in various activities and communicate with each other.

Such is the CS professor. Hangang Tong He described the related research interests of the three collaborative projects in which he is involved. His participation in these groups has earned him a Multidisciplinary University Research Initiative (MUR) from the US Air Force, a grant from the National Science Foundation, and a Visa Faculty Award. The MURI grant, “Understanding Social Networking Online/Offline Behavior Dynamics: From Data to Models to Predictions,” is a joint project between the University of Michigan, Princeton University, and the University of Illinois at Urbana-Champaign. Prof Rayadurgam Srikanth. and Tong Illinois are members of the group.

“A key component of this Air Force grant is called graph matching, or network alignment,” Tong said. The idea is that if we can somehow match people in the online virtual world with people in the physical world, this will provide a key link that will help further analysis. For example, you want to know if what certain people say or interact with in the online world triggers something in the physical world. The team’s proposal holds challenges in mathematical computer science and electrical engineering. As Tong puts it, “This mathematical problem is not a simple problem from an algorithmic perspective, graph matching or alignment. It is a very difficult problem in classical graph theory. But we want to do more than that. It’s what we call diversity. The basic assumption of classical graph matching is to assume that people behave more or less the same way in two different worlds. Our task is to try to recover this kind of consistent behavior and connect them together. But what we are facing here is much more complicated. How can we develop an algorithm to connect people together? Although they show different behavior. I’m excited here; This project comes from three different universities and we all have different backgrounds, we hope we can do something interesting together.

The NSF-funded project is “Reconstructing Transmission History in Cyber ​​and Human Networks with Applications in Epidemiology and Cybersecurity.” Tong is collaborating with Michigan colleague Lei Ying, who works on the theoretical side of the algorithm and the application side.

Tong called the Visa Faculty Award program “very exciting.” The Illinois CS project team has been working with visa researchers on the financial application. “The real reason we got this recognition is mainly because of our students and the amazing research they’ve done in the past,” said Tong. This is especially true for visa faculty awards. It comes across as a faculty award, but it’s really recognizing graduate students.”

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