Research

My work aims to expand our understanding of fundamental social phenomena such as cooperation, contagion, and inequality. Theoretically, I focus on identifying mechanisms and accounting for complex dynamics. Methodologically, I take advantage of the research opportunities opened by new computational and online technologies.

Most of my recent research experience has involved designing and developing online experiments. My PhD dissertation used online experiments to disentangle two distinct mechanisms for the contagion of prosocial and antisocial behavior. The experiment design was novel in that it allowed crowd-sourced subjects from Amazon Mechanical Turk to interact with each other repeatedly over time. I was also involved in a project that used a web-based real-time multi-player game to test the predictions of the Schelling model of segregation for different utility functions.

Another large portion of my work involves computational modeling. One chapter of my PhD dissertation uses a threshold model with dynamic interaction structure and adaptive behavior to simulate a population of agents with the behavior we found in the online experiment. Another computational project in which I participated investigated the effect of gossip on social networks.

I am also involved with network analysis, in particular, the analysis of temporal networks. This has constituted the majority of my postdoctoral research at the Oxford Internet Institute. In one project, I analyzed temporal motifs in the network of reverts on Wikipedia in order to uncover negative social interactions such as direct retaliation and generalized retaliation. In another project, I modeled reverts between two editorsĀ  over time as interaction trajectories and used unsupervised machine learning to compare how bots on Wikipedia differ in their interactions from human editors.