Online social contagion modeling through the dynamics of Integrate-and-Fire neurons

We introduce a novel model capturing the dynamics of the online social contagion. We adopt a neuroscience perspective and consider the online social networks analogous to networks of Integrate-and-Fire neurons. The dynamics of the model is driven by three sources of positive or negative influence: The individuals' self-generated bias, the interpersonal online interactions, and the external environment stimulus. The model explains the online activity growth and the activity propagation patterns in relation to the interaction network, the endogenous and exogenous influence, and the individuals' activation mechanism. Through simulation experiments and validation against empirical data from Twitter, we demonstrate that the model captures the relationship between the dynamically changing internal and external influence and the ensuing online activity. As such, it can accurately reproduce collective activity patterns arising from the online users' response to various kinds of stimuli. The model can be generalized to handle a wide class of contagion phenomena. (C) 2015 Elsevier Inc. All rights reserved.