I study collective outcomes in social networks, examining how network structure and strategic incentives shape belief formation, cooperation, and conflict. My research combines microeconomic theory, experiments, and data-driven approaches to understand when networks succeed in aggregating information and sustaining coordination, and when they fail.
Published
“Enhancing Resiliency and Promoting Prosocial Behavior among Tanzanian Primary-School Students: A School-Based Intervention” (with R. Berger, J. Benatov, R. Cuadros, and M. Gelkopf). Transcultural Psychiatry, 2018, 55(6): 821-845. [PDF] [DOI]
Children in Sub-Saharan Africa face chronic adversity but often lack access to mental health care. We evaluate a culturally adapted school-based intervention designed to enhance resiliency and prosocial behavior among Tanzanian primary school students. Students randomly assigned to the intervention showed significant improvement across all outcomes of social difficulties, anxiety, school functioning, and prosocial behaviors both post-intervention and at 8-month follow-up.
Under Review
“Cooperation in a Dynamic Network” (with Nicole Immorlica, Brendan Lucier, and Brian W. Rogers). [PDF]
We study cooperation in evolving networks where agents play repeated prisoner’s dilemma games and can sever relationships. We characterize simple stationary equilibria in which cooperation and defection coexist even as players become arbitrarily patient, capturing the observation that many social networks exhibit high but not universal cooperation. Low levels of cooperation can be sustained only through exclusivity among cooperating agents.
Working Papers
“Belief Formation on Networks” (with Junya Murayama, Brian W. Rogers, and Xiannong Zhang). [PDF]
We design laboratory experiments to study how people combine interdependent information sources. About half of subjects solve problems where source values can be exactly deduced, but essentially none solve structurally similar problems with non-degenerate posteriors. Success in the former does not predict performance in the latter. Most subjects fail to identify even directional effects of signals, suggesting their success relies on fragile heuristics rather than robust understanding.
Work in Progress
“Learning Who to Trust: A Joint Inference Theory of Persistent Disagreement” [Draft available upon request]
This paper offers an explanation for persistent disagreement based on joint inference rather than cognitive biases or non-standard preferences. When agents must simultaneously learn what is true and whom to trust, observed disagreement becomes rational evidence of low source reliability. This trust erosion fragments networks and prevents consensus, providing Bayesian microfoundations for belief fragmentation and information echo chambers in social learning.
“Linguistic Distance, Societal Structure, and Civil War.” [Draft available upon request]
A substantial literature finds that ethnic polarization predicts civil conflict, but existing measures treat all ethnic divisions as equally salient. This paper incorporates linguistic distance as a proxy for cultural distance and uses spectral graph partitioning to endogenously identify each country’s dominant ethnic cleavage. The resulting Spectral Polarization index significantly outperforms traditional measures in predicting propensity for civil conflict.
“Group Targeting in Homophilous Networks.”
Optimal network seeding requires detailed individual-level data rarely available to policymakers. This paper develops a targeting framework that exploits group-level homophily to design multi-stage interventions using only aggregated data. By transforming the individual-level optimization into a shortest-path computation at the group level, the approach achieves 15-35% cost reductions relative to uniform seeding.
“The Effects of Media Sentiment on Product Sales: Evidence from the Soft Drinks Industry” (with Sumedha Rajbanshi).
We estimate the effect of media sentiment on soft drink sales in New York State. Using natural language processing to analyze media coverage of Coca-Cola and PepsiCo (2006-2012), we find lagged sentiment significantly predicts sales, with stronger effects for core products bearing the firm name. These findings suggest that brand salience moderates consumer response to reputational information.
