A trust model for spreading gossip in social networks: a multi-type bootstrap percolation model

Abstract

We introduce here a multi-type bootstrap percolation model, which we call T -Bootstrap Percolation (T -BP), and apply it to study information propagation in social networks. In this model, a social network is represented by a graph G whose vertices have different labels corresponding to the type of role the person plays in the network (e.g. a student, an educator, etc.). Once an initial set of vertices of G is randomly selected to be carrying a gossip (e.g. to be infected), the gossip propagates to a new vertex provided it is transmitted by a minimum threshold of vertices with different labels. By considering random graphs, which have been shown to closely represent social networks, we study different properties of the T -BP model through numerical simulations, and describe its implications when applied to rumour spread, fake news, and marketing strategies.

Housing market forecasts via stock market indicators

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Cell fusion through slime mould network dynamics

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Cell fusion through slime mold network dynamics

“…(b) Multiple CELLs can be used to model the spread of knowledge among groups of people. Following the ideas of [1], certain groups would begin with certain knowledge, and when they encounter another group, they would combine and both share the knowledge possibly modified. In such way, one could potentially understand the spread and deformation of ideas and information.…”