Research in the Human Nature Lab lies at the intersection of the natural, social, and computational sciences. We develop and apply novel insights about the aspects of human nature that relate to our interactions with others. Our concern is not so much with how humans think or behave while alone, but rather with how they think and feel about, and behave towards, others.  We are interested in the emergent properties of social systems, and their social and evolutionary origins.


Our greatest aspiration in the HNL is to see new things. Sometimes, we see old things in new ways. But either way, our principle mode of communication is to publish our work in scientific journals.

All Publications


Good science often involves developing new tools. We make tools we develop publicly available here.


Breadboard is a software platform for developing and conducting human interaction experiments in groups.

More about Breadboard →


Trellis is a suite of software tools for developing, administering, and collecting survey and social network data.

More about Trellis →

Network Visuals

Below is a selection of network visualizations.

All Network Visualizations


The sponsors of our work, and a sketch of projects they are supporting, are listed here. 

Exploiting Social Influence in Networks to Magnify Population-Level MNCH Behavior Change

We will use a detailed understanding of social network structure and function to identify novel ways of targeting influential individuals so as to foster behavioral cascades and population-level behavior change. We will achieve this objective by conducting a randomized controlled trial of network targeting algorithms, to be deployed in a sample of 160 villages in Honduras, with maternal and neonatal care interventions.

Roybal Center for the Study of Social Networks and Well Being (one of Roybal Centers for Translational Research on Aging)

Our Roybal Center is focused on the recognition that complex social network structures play an important role in individual health. The two overarching goals of our work are (1) to ask significant questions about the role of social networks in producing specific outcomes related to health and well-being, and (2) to develop methods of answering such questions involving real social networks in which behavioral information relevant to health and wellbeing can be measured.

In our prior Program Project, “Networks and Neighborhoods,” which unfolded from 2008-2014 and which has already yielded over 73 publications and 9,300 citations to date, we contributed to illuminating fundamental biological and social mechanisms related to the structure and function of human social networks. But eventually, we began to engage what we called our “so what?” question. Namely: So what if we can understand the structure and function of human social networks; what can we do with that knowledge to make the world better? And, indeed, since 2010, with gathering steam, we’ve been exploring how a deeper understanding of social networks allows us to intervene in the world to make it better, by improving health, cooperation, innovation, wealth, and social life. 

Yale University and the Tata group have launched a far-ranging research collaboration that builds on their shared strengths in discovery, technology, and innovation. The alliance is led at Yale by Nicholas Christakis ’84, co-director of the Yale Institute for Network Science (YINS) and the Sol Goldman Family Professor of Social and Natural Science. The Tata group has committed to fund the alliance over five years. The project will foster an intellectual exchange between the university and three Tata companies: Tata Sons, Tata Consultancy Services, and Tata Chemicals. 

Prior funding from RWJF afforded us the opportunity to explore the relationship between social networks and health in new ways. For example, we assessed network structure and health on a national scale, evaluated the utility of a novel “sensor network” approach to predicting epidemics, and investigated how the structure and function of online networks is relevant to health and behavior change. Funding from RWJF also helped us develop new software tools that will significantly increase the accuracy of network data collection in the field while lowering its cost.