Navigating the Interdisciplinary Frontier: Computational Social Science and Public Agenda Dynamics
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Computational social science (CSS) has spearheaded a transformative era in research, permeating every facet of the social sciences. CSS stands as an intersection, seamlessly merging computational algorithms and statistical methodologies from computer science and statistics with the rich tapestry of theoretical concepts and frameworks drawn from diverse social science disciplines. In this talk, I embark on a decade-long research journey that delves into the intricate realm of public agenda dynamics—a seemingly simple yet profoundly intricate facet of public opinion research. Our expedition begins with two comprehensive studies rooted in expansive social media datasets: one reevaluating the conventional issues competition theory and another introducing and assessing an innovative issues coopetition model. Furthermore, I unveil our most recent endeavor—an innovative ecological perspective that unravels the intricate web of interissue relationships on the public agenda. This perspective was empirically tested using Gallup Most Important Problem (MIP) polls spanning from 1958 to 2020 in the United States. Through this lens, I illuminate how CSS reinvigorates our understanding of existing and emerging questions within the realm of social science. Lastly, I explore the dynamic synergy of interdisciplinary integration within CSS, highlighting its potential to redefine the landscape of social science research and education.