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. 2014 Mar 11:4:4343.
doi: 10.1038/srep04343.

The simple rules of social contagion

Nathan O Hodas  1 , Kristina Lerman  1
Affiliations

The simple rules of social contagion

Nathan O Hodas et al. Sci Rep. .

Abstract

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.

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Figures

Figure 1
Figure 1. The exposure response functions for Twitter and Digg, (a) as a function of total number of votes for the URL a user receives in their information stream, and (b) as a function of the fraction of friends adopting story, for Digg only.
The equivalent results for Twitter can be found in.
Figure 2
Figure 2. The time response functions for (a) Digg and (b) Twitter for different user classes.
Figure 3
Figure 3. The social enhancement factors for Twitter and Digg.
(a,c) Averaged over all users, (b,d) Calculated for sub-populations based on nf. The decay in the social enhancement factor for Twitter can be attributed to residual spam in the dataset.
Figure 4
Figure 4. Forecasting accuracy for Twitter and Digg.
See this image and copyright information in PMC

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