Johan Ugander, Experiments with Network Effects
Автор: ICMEStudio
Загружено: 2016-05-27
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Experiments with Network Effects
Johan Ugander, Assistant Professor of Management and Sciences Engineering, Stanford University
A/B testing is a standard approach for evaluating online experiments; the goal is to estimate the "average treatment effect" of a new feature or condition by exposing a sample of the overall population to it. A drawback with A/B testing is that it is poorly suited for experiments involving social interference, when the treatment of individuals spills over to neighboring individuals along an underlying social network. This video features a discussion of recent work on this problem, including how randomization techniques that administer treatments at the level of graph clusters can significantly reduce the bias and variance of experiments in highly networked settings.
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