I am a computational sociologist and a PhD candidate in the dual-title Sociology and Social Data Analytics (STEM) PhD program at The Pennsylvania State University, where I work with Daniel Dellaposta and David Baker.
I use qualitative, quantitative, and computational methods (e.g., agent-based modeling, epidemiological methods, spatial econometrics, machine learning, natural language processing and network analysis, among other techniques) to understand collective behavior. I love putting together new ‘big’ datasets, and usually aim for applying cutting edge methods combined with social theoretical rigor in analyzing unique cases (see. ongoing projects).
My work has appeared in Nature Scientific Data, Canadian Public Policy, Frontiers in Political Science, Journal of Political Institutions and Political Economy, and Review of Development Economics, and has been featured in U.S.News, Haaretz, The Conversation, EurekAlert!, Cosmos Magazine, Phys.org, and other media outlets. I currently have at least 6 papers under review at various journals.
I am an alumnus of Istanbul Şehir University (RIP), where I studied Political Science and International Relations, Sociology, and Psychology. I have also spent an exchange semester at the University of Bamberg, Germany. I also have an MA in Political Science from the State University of New York at Binghamton (where I received a Dissertation Year Award and taught two original courses).
My MA thesis (under review at American Sociological Review) on the diffusion of lynchings in India has received (1) Huber-Form MA Thesis Award from the Pennsylvania State University, and (2) Robert F. Dentler Student Practitioner Award and (3) Elise Boulding Student Paper Award from the American Sociological Association’s Public Sociology and Sociological Practice, and Peace, War and Social Conflict sections, respectively (other awards and honors).
My dissertation project bridges many academic fields (Sociology, Psychology, and Business Management) and methodologies (inferential statistics, machine learning, network analysis, and natural language processing). It deals with the dynamics of creativity and innovation (i.e., interaction among the producers, consumers, and evaluators) in cultural markets (i.e., ideas, music, movies, novels, video games, etc.) using original, massive datasets (network ties, text, rankings etc.). Specifically, I deal with questions concerning collaborations, status dynamics, knowledge spillover, and symbolic boundaries in creative industries using a massive (perhaps the largest privately held dataset) of 40m+ songs attributed to 1m+ artists. My dissertation committee includes Daniel Dellaposta (Chair), Diane Felmlee, Charles Seguin, and Stephen Humphrey.
I spend my free time as an independent consultant on two public sector projects in the Middle East, and part of team helping lawyers choose winning cases using AI and predictive analytics. I have also served on various administrative positions in and outside academia.
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