Abstract
Social networks underly a broad range of social and economic research questions that are increasingly being understood through large-scale computational analyses. In particular, the study of social influence and information diffusion on social networks have rich modeling histories, while opportunities in online instrumentation and experimentations are now providing tremendous advances in our abilities for theory testing as well as theory development. This tutorial will provide a brief overview of models of social networks and social influence, and then focus on giving an overview of recent evidence for how these processes behave empirically in diverse online settings. A particular emphasis will be placed on efforts to approach these problems through causal inference, moving beyond "big data" to "big experimentation".
Slides
Slides PDF (15.6 MB)
References
(Not all these references are mentioned on the slides; some came up extemporaneously during discussions at the EC tutorial.)
Early work:
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Part I: From Theory to Data
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Part II: Causal Inference and Experimentation
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