Stochastic Modeling of the Decay Dynamics of Online Social Networks

Abstract

The dynamics of online social networks (OSNs) involves a complicated mixture of growth and decay. In the last decade, many online social networks, like MySpace and Orkut, suffered from decay until they were too small to sustain themselves. Thus, understanding this decay process is crucial for many scenarios that include: (1) Engineering a resilient network, (2) Accelerating the disruption of malicious network structures, and (3) Predicting users leave dynamics. In this work we are interested in modeling and understanding the decay dynamics in OSNs to handle the aforementioned three scenarios. Here, we present a probabilistic model that captures the dynamics of the social decay due to the inactivity of the members in a social network. The model is proved to have submodularity property. We provide preliminary results and analyse some properties of real networks under decay process and compare it to the model’s results. The results show, at the macro level of the networks, that there is a match between the properties of the decaying real networks and the model.