Measuring Social Influence Without Bias
نویسنده
چکیده
How well can statistical models disentangle the effects of social influence from homophily in observational network data, and under what conditions do they models fail?1 Many outcomes of interest to social scientists – such as obesity, political attitudes, altruism, and drug use – are highly correlated within social networks.2 However, behaviors and attitudes tend to be correlated in social networks for reasons other than just direct peer-to-peer influence, resulting in serious methodological challenges for making causal inferences in purely observational data (Angrist, 2014; Manski, 1993).
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