Event Date
Emily Chen
Human Behavior in Systems that Undergo Change
Abstract: What happens to the way we, as individuals and communities, behave when the systems we interact with undergo sudden change or shock? Throughout my research, I have tackled this question by examining behavior through two distinct lenses: what people explicitly say, and what they implicitly do. To answer these questions, I have built and analyzed large-scale, longitudinal datasets from social media platforms like Twitter (X) and online multiplayer games like League of Legends, which span from a single year to multiple years' worth of data. In this talk, I will begin by looking at how explicit communication in communities was affected by information flow during the COVID-19 pandemic and political events, focusing on community structures in the context of misinformation and polarization. I will then shift to exploring how video games can serve as a setting to study implicit behavior, highlighting the interplay between personal agency and structural incentives. Ultimately, this presentation aims to provide insight into how a more nuanced understanding of human behavior—both explicit and implicit—in rapidly evolving socio-technical landscapes can open new avenues for data-driven decision-making in policy and design.
Bio: Emily Chen is a 6th-year PhD candidate at the University of Southern California, advised by Professor Emilio Ferrara. She is an active member of the HUMANS (HUmans, MAchines, and Networks in Society) Lab, as well as the Annenberg Game Lab led by Professor Dmitri Williams. Her research focuses on computational social science and AI for social good, particularly within areas of social network analysis, online communities and behavioral studies. Her work leverages large-scale datasets from social media platforms and online games to explore how community dynamics and structures evolve and how behaviors shift in socio-technical platforms. Her recent projects center on using online multi-player video games to examine how behaviors adapt and persist both across and within the same platforms. Emily’s work has been published in venues such as ICWSM, CSCW, JMIR, the Harvard Kennedy School Misinformation Review and the Journal of Computational Social Science, and has been featured by The New York Times, PsyPost, Undark and Forbes India. She received the USC Viterbi School of Engineering Best Computer Science Research Assistant Ph.D. Award in 2021.