Social Influence Field Experiments in Networks: Models and considerations
Date and Time: Thursday, June 27 (1-5 pm)
Room: Dogwood
Description
Estimating the strength of social influence within social networks is extremely difficult due to selection processes, homophily, and mutual causation. The power of randomization is used by experiments to side-step these analytic challenges in most setting, but social networks pose a special challenge for field experiments. This workshop introduces students to the logic of experimentation, presents three analytic archetypes for conducting experiments in real world social networks, and provides guidance on the analysis. Topics covered will include the Rubin Causal Model and randomization inference.
Instructor
David Nickerson is an associate professor of political science at the University of Notre Dame. He uses experiments to study how campaigns can best mobilize people to vote, volunteer, and donate.
Required equipment/software
Workshop examples will use Stata, but all are easily adapted for R.