11/28/2023 Bruce Adams
CS professor Hanghang Tong is part of three teams receiving research grants from the U.S. Air Force, NSF, and Visa. Each is looking into how people interact with each other on social media compared to the physical world.
Written by Bruce Adams
“We want to use the graph algorithm to understand human behavior in two worlds. One is in 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 interact with each other.”
That’s how CS Professor Hanghang Tong described the linked research interests of three collaborative projects he is involved in. His involvement in these groups has resulted in a Multidisciplinary University Research Initiative (MUR) grant from the U.S. Air Force, a National Science Foundation grant, and a Visa Faculty Award. The MURI grant is for “Understanding Social Network-Transcendent Online/Offline Behavioral Dynamics: From Data to Models to Prediction,” a joint project between the University of Michigan, Princeton University, and the University of Illinois Urbana-Champaign. Professor Rayadurgam Srikant and Tong are Illinois members of the team.
Tong said that “for this Air Force grant, one key component is called graph matching, or the network alignment. The idea is that if we can somehow align people in the online virtual world with people in the physical world, then this will provide a key linkage to help with the subsequent analysis. For example, you want to identify if what some people say or interact within the online world will trigger something in the physical world.” The team’s proposal takes on challenges in mathematics, computer science, and electric engineering. As Tong put it “this problem of mathematics from the algorithm perspective, the graph matching or alignment is not an easy problem. It's a very hard problem in classic graph theory. But what we want to do is more than that. It is something we call disparity. The underlying assumption of the classic graph matching is that we assume people have more or less the same behavior across two different worlds. Our task is to try to recover this kind of consistent behavior so that we can link them together. But what we are facing here is much more complicated. How can we develop an algorithm to link people together? Even if they exhibit disparity behavior. I'm excited here; this project comes from three different universities, and we all have quite different backgrounds hopefully, we can do something interesting together.”
The NSF-funded project is “Reconstruction of Diffusion History in Cyber and Human Networks with Applications in Epidemiology and Cybersecurity”. Tong is collaborating with a Michigan colleague, Lei Ying, who will work on the theoretical side while Tong works on the algorithm and application side.
Tong calls the Visa Faculty Award program “something I also enjoyed a lot.” The Illinois CS project team has been collaborating with Visa researchers working on the financial application. “The real reason that we got this recognition,” Tong noted, “is largely because of our students and the wonderful research they have done in the past. This is especially true for the Visa Faculty Award. It comes as a faculty award, but it's really recognizing the graduate students.”