| Literature DB >> 32271857 |
Rinni Bhansali1, Laura P Schaposnik2,3.
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.Entities:
Keywords: bootstrap percolation; disease propagation; information propagation; trust model
Year: 2020 PMID: 32271857 PMCID: PMC7125993 DOI: 10.1098/rspa.2019.0826
Source DB: PubMed Journal: Proc Math Phys Eng Sci ISSN: 1364-5021 Impact factor: 2.704