[#46] Structurally Distorted Communication in a Population & Interdisciplinary Research Done Right

Sagar Kumar
Mar 13, 2025 Seminar
Talk recording

Many of today’s most pressing issues require a more robust understanding of how information spreads in populations. Current models of information spread can be thought of as falling into one of two varieties: epidemiologically-inspired rumor spreading models, which do not account for the noisy nature of communication, or information theory-inspired communication models, which do not account for spreading dynamics in populations. The viral proliferation of misinformation and harmful messages seen both online and offline, however, suggests the need for a model that accounts for both noise in the communication process, as well as disease-like spreading dynamics.

Since beginning my research career, I have been fortunate enough to be part of studies which fall in the realm of communication, epidemiology, psychology, microbiology, natural language processing, and beyond. As complex systems scholars, we are both afforded the luxury and condemned with the curse of interdisciplinarity. As a graduate student, this can be both liberating and terrifying. In out discussion, we will engage in a conversation about: how true interdisciplinary research begins with a question, how shiny new methods can easily distract us, and how a little bit of humility can unlock countless doors.

This week, we had the pleasure of hosting Sagar Kumar, a 3rd year Ph.D. student from the Network Science Institute at Northeastern University. Sagar’s research focuses on the intersection of communication theory and mathematical modeling.

This week, Sagar spoke about his recent pre-print, “A Unifying Model of Information Loss in Communication Across Populations”, which is an attempt to bridge two different approaches to the study of information spread. The first approach is an information theory-inspired approach, which focuses on communication as a noisy process. The second approach is an epidemiology-inspired approach, which focuses on the spread of information in populations. While these mechanisms usually appear separately, Sagar’s work asks, “what happens when these mechanisms are considered together?”

To demonstrate the framework, Sagar showed results from several different examples of noisy spreading channels—including symmetric and assymetric channels—and investigated how the differences in these lead to vastly different levels of information loss in the system.

In the discussion, Sagar shared his experiences working on interdisciplinary projects, and how he navigates the challenges of working across different fields. The conversation focused on the tradeoff between focusing on developing new and fancy methods to solve a problem, versus developing expertise in a problem domain and a clear question and then finding the right methods to solve it. Sagar empahsized that that starting with a clear question can unlock opportunities to foucs on new and interesting method. However, and although these approaches are not mutually exclusive, we discussed how understanding and naviating this tension is a criticial skill when doing interdisciplinary work.

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