Add to ORKGThe Spatial Preferential Attachment model is a spatial random graph used to model social networks. Nodes live in a metric space, and edges are formed based on the metric distance and degree of the nodes. Rumour spreading is a protocol for the spread of information through a graph. In each time step nodes can pass the rumour to only one of their neighbours. The spread time is the expected time when all nodes have the rumour. We analyze rumour spreading on the SPA model, and show that the spread time differs substantially from the diameter. Joint work with Jeannette Janssen.Non UBCUnreviewedAuthor affiliation: University of British ColumbiaPostdoctora
We consider the popular and well-studied push model, which is used to spread information in a given ...
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...
1. The ground is a simple connected graph. 2. At time 0, one vertex knows a rumour. 3. At each time-...
The Spatial Preferential Attachment model is a spatial random graph used to model social networks. N...
We introduce a general stochastic model for the spread of rumours, and derive mean-field equations t...
Social networks are an interesting class of graphs likely to become of increasing importance in the ...
Abstract. We investigate a stochastic model for complex networks, based on a spatial embedding of th...
<p>We investigate a stochastic model for complex networks, based on a spatial embedding of the nodes...
This study aims at developing a non-(semi-)parametric method to extract the hidden network structure...
© Springer Nature Switzerland AG 2018. In this paper, we propose a modified susceptible-infected-rem...
In this work; three specific dynamical systems models, the Basic, Maki-Thompson, and Daley-Kendall, ...
AbstractSocial networks are an interesting class of graphs likely to become of increasing importance...
Spreading processes are ubiquitous in natural and artificial systems. They can be studied via a plet...
Abstract. We present a new stochastic model for complex networks, based on a spatial embedding of th...
We show that if a connected graph with n nodes has conductance φ then rumour spreading, also known a...
We consider the popular and well-studied push model, which is used to spread information in a given ...
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...
1. The ground is a simple connected graph. 2. At time 0, one vertex knows a rumour. 3. At each time-...
The Spatial Preferential Attachment model is a spatial random graph used to model social networks. N...
We introduce a general stochastic model for the spread of rumours, and derive mean-field equations t...
Social networks are an interesting class of graphs likely to become of increasing importance in the ...
Abstract. We investigate a stochastic model for complex networks, based on a spatial embedding of th...
<p>We investigate a stochastic model for complex networks, based on a spatial embedding of the nodes...
This study aims at developing a non-(semi-)parametric method to extract the hidden network structure...
© Springer Nature Switzerland AG 2018. In this paper, we propose a modified susceptible-infected-rem...
In this work; three specific dynamical systems models, the Basic, Maki-Thompson, and Daley-Kendall, ...
AbstractSocial networks are an interesting class of graphs likely to become of increasing importance...
Spreading processes are ubiquitous in natural and artificial systems. They can be studied via a plet...
Abstract. We present a new stochastic model for complex networks, based on a spatial embedding of th...
We show that if a connected graph with n nodes has conductance φ then rumour spreading, also known a...
We consider the popular and well-studied push model, which is used to spread information in a given ...
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...
1. The ground is a simple connected graph. 2. At time 0, one vertex knows a rumour. 3. At each time-...