Social decision making - from voting in a national election to investing in the stock market - is fundamental to human behavior. But the outcome of social decisions are notoriously hard to predict. Even in a simple setting, such as the Prisoner’s Dilemma, the result depends on a complex interplay between the assumptions, intentions and understanding of two individuals. When social decisions play out across a whole social network the dynamics can become dauntingly complex. Yet understanding how a social network structures the information environment, and the resulting effects on individual and collective decisions, is an increasingly urgent challenge.

In this talk I will give a brief overview of my research building mathematical and computational models as tools to study collective decisions, inter-group attitudes and prosocial behavior. I will describe my recent work using a combination of game-theoretic modeling, online experiments and analysis of social network data to predict outcomes in a voter game. I will show how such games naturally produce intransigent zealots, and how superficially ``fair’’ social networks can nonetheless lead to heavily biased collective decisions - a phenomenon we call information gerrymandering. Finally I will discuss my plans for future research and collaborations, to study how individual behavioral and population dynamics play out on complex social networks.