| Contents |
| Understanding the collective reaction to individual actions is key to effectively
spread information in social media. In this work we define efficiency on Twitter,
as the ratio between the emergent spreading process and the activity employed by
the user. We characterize this property by means of a quantitative analysis of the
structural and dynamical patterns emergent from human interactions, and show it
to be universal across several Twitter conversations. We found that some influential
users efficiently cause remarkable collective reactions by each message sent, while
the majority of users must employ extremely larger efforts to reach similar effects.
Next we propose a model that reproduces the retweet cascades occurring on Twitter
to explain the emergent distribution of the user efficiency. The model shows that the
dynamical patterns of the conversations are strongly conditioned by the topology
of the underlying network. We conclude that the appearance of a small fraction of
extremely efficient users results from the heterogeneity of the followers network and
independently of the individual user behaviour. |
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