Papers
Topics
Authors
Recent
Search
2000 character limit reached

Generalized Voter-like model on activity driven networks with attractiveness

Published 20 Apr 2018 in physics.soc-ph | (1804.07476v1)

Abstract: We study the behavior of a generalized consensus dynamics on a temporal network of interactions, the activity driven network with attractiveness. In this temporal network model, agents are endowed with an intrinsic activity $a$, ruling the rate at which they generate connections, and an intrinsic attractiveness $b$, modulating the rate at which they receive connections. The consensus dynamics considered is a mixed voter/Moran dynamics. Each agent, either in state $0$ or $1$, modifies his/her state when connecting with a peer. Thus, an active agent copies his/her state from the peer (with probability $p$) or imposes his/her state to him/her (with the complementary probability $1-p$). Applying a heterogeneous mean-field approach, we derive a differential equation for the average density of voters with activity $a$ and attractiveness $b$ in state $1$, that we use to evaluate the average time to reach consensus and the exit probability, defined as the probability that a single agent with activity $a$ and attractiveness $b$ eventually imposes his/her state to a pool of initially unanimous population in the opposite state. We study a number of particular cases, finding an excellent agreement with numerical simulations of the model. Interestingly, we observe a symmetry between voter and Moran dynamics in pure activity driven networks and their static integrated counterparts that exemplifies the strong differences that a time-varying network can impose on dynamical processes.

Citations (16)

Summary

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.