Complex contagion features without social reinforcement in a model of social information flow
Pond, Tyson
Pond, Tyson
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Abstract
Contagion models are a primary lens through which we understand the spread of information over social networks. However, simple contagion models cannot reproduce the complex features observed in real world data, leading to research on more complicated complex contagion models. A noted feature of complex contagion is social reinforcement, that individuals require multiple exposures to information before they begin to spread it themselves. Here we show that the quoter model, a model of the social flow of written information over a network, displays features of complex contagion, including the weakness of long ties and that increased density inhibits rather than promotes information flow. Interestingly, the quoter model exhibits these features despite having no explicit social reinforcement mechanism, unlike complex contagion models. Our results highlight the need to complement contagion models with an information-theoretic view of information spreading to better understand how network properties affect information flow and what are the most necessary ingredients when modeling social behavior.
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11:00am-1:00pm
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Date
2020-01-01