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The Case for Causality. Betsy Sinclair University of Chicago IGNITE, PolNet 2012, Boulder. The Political Networks Community. Has been extremely successful at generating new theories about the implications of social interaction
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The Case for Causality Betsy Sinclair University of Chicago IGNITE, PolNet 2012, Boulder
The Political Networks Community... • Has been extremely successful at generating new theoriesabout the implications of social interaction • Has pioneered the collection and use of social network data • …and still has some work to do in terms of identifying cause and effect Our subfield’s toughest critics are concerned that we confound social influence and homophily.
“If your friend jumped off a bridge, would you jump too?” (Shalizi and Thomas 2011) • Homophilyandsocial influence are typically confounded. • This problem is further complicated as individuals are more likely to be influenced by similar alters.
Solutions 1. Already have the right data: • Include all appropriate control variables • Control-by-cluster 2. Generate better data: • Randomize over the network 3. Use the data you already have: • Sensitivity Analysis
The Case for Robust Inference • What if there is strong evidence for social influence? • We silence many of our critics • We can begin to theorize about the instances influence occurs • What if there is limited evidence for social influence? • This generates new theoretical avenues for us to pursue • Are people sorting themselves into social networks with higher levels of homophily then we originally suspected? • Why would individuals prefer networks with homophily, particularly if we see limited evidence of social influence?