The concept of contagion has steadily expanded from its original grounding in epidemic disease to describe a vast array of processes that spread across networks, notably social phenomena such as fads, political opinions, the adoption of new technologies, and financial decisions. Traditionalmodels of social contagionhave been based on physicalanalogieswithbiological contagion, inwhichtheprobability that an individual is affected by the contagion growsmonotonically with the size of his or her “contact neighborhood”—the number of affected individualswithwhomhe or she is in contact.Whereas this contact neighborhood hypothesis has formed the underpinning of essentially all current models, it has been challenging to evaluate it due to the difficulty in obtainingdetailed dataonindividual network neighborhoods during the course of a large-scale contagion process. Here westudy this question by analyzing the growth of Facebook, a rare example of a social process with genuinely global adoption.We find that the probability of contagion is tightly controlled by the number of connected components in an individual’s contact neigh- borhood, rather than by the actual size of the neighborhood. Sur- prisingly, once this “structural diversity” is controlled for, the size of the contact neighborhood is in fact generally a negative predictor of contagion. More broadly, our analysis shows how data at the size and resolution of the Facebook network make possible the identifi- cationofsubtle structural signals thatgoundetectedatsmaller scales yet hold pivotal predictive roles for the outcomes of social processes.
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