document: Differences in the mechanics of information diffusion across topics : idioms , political hashtags , and complex contagion on twitter There is a widespread intuitive sense that different kinds of information spread differently on-line , but it has been difficult to evaluate this question quantitatively since it requires a setting where many different kinds of information spread in a shared environment . Here we study this issue on Twitter , analyzing the ways in which tokens known as hashtags spread on a network defined by the interactions among Twitter users . We find significant variation in the ways that widely-used hashtags on different topics spread . Our results show that this variation is not attributable simply to differences in `` stickiness , '' the probability of adoption based on one or more exposures , but also to a quantity that could be viewed as a kind of `` persistence '' - the relative extent to which repeated exposures to a hashtag continue to have significant marginal effects . We find that hashtags on politically controversial topics are particularly persistent , with repeated exposures continuing to have unusually large marginal effects on adoption ; this provides , to our knowledge , the first large-scale validation of the `` complex contagion '' principle from sociology , which posits that repeated exposures to an idea are particularly crucial when the idea is in some way controversial or contentious . Among other findings , we discover that hashtags representing the natural analogs of Twitter idioms and neologisms are particularly non-persistent , with the effect of multiple exposures decaying rapidly relative to the first exposure . We also study the subgraph structure of the initial adopters for different widely-adopted hashtags , again finding structural differences across topics . We develop simulation-based and generative models to analyze how the adoption dynamics interact with the network structure of the early adopters on which a hashtag spreads .
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