My research features empirical analyses of large behavioral data sets, with an eye toward longitudinal and network-based processes. I also use agent-based models, social simulation, and formal mathematics to develop insights on social behavior.
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​Networks and Trajectories in Boundaryless Careers

Careers that typically unfold across or outside of organizations, "boundaryless careers", can shed insight on how individuals and networks co-evolve with one another. Analyzing patterns of interactions can also reveal how different industries and occupational spheres evolve over time.

Using data sets from the worlds of sports and entertainment, my research currently examines how individuals may benefit from interacting with the certain people in their profession as well as their position in larger networks, and how the motives of social interaction change over time in different contexts.
Network of fist-fights in the NHL from 2008-12 occurring after a face-off (top, red), versus occurring after a non-fighting penalty (bottom, blue).
 ​Social Coordination and Cohesion

Successful groups and societies are characterized by high levels of coordination and pro-social behavior. Using simulations and agent-based models, I examine how the formation of expectations, contests for status, and social inequality can either help or hinder social coordination. I also empirically examine the motives of peer-sanctioning and peer-rewarding - important tools of social cohesion - through the context of online review systems.


​Homophily and Network Sampling

Homophily, the tendency for similar individuals to associate with one another, is a seemingly ubiquitous feature of many societies.
Large online traces of social networks can improve our estimates of the levels of segregation and integration between different groups in society. Conversely, respondent-driven sampling (RDS), a network-sampling technique that is used by sociologists and public health workers, leverages the phenomenon of homophily to gather information about hidden and hard-to-reach populations. My work involves studying rates and patterns of interaction between different online groups, improving RDS performance, and adapting RDS for use in the study of online populations.