@article{Schweitzer2020,
author = "Schweitzer, Frank",
title = "Social percolation revisited: From 2d lattices to adaptive network",
journal = "Physica A",
doi = "https://doi.org/10.1016/j.physa.2020.125687",
url = "https://www.sciencedirect.com/science/article/pii/S0378437120309857",
abstract = "The social percolation model (Solomon et al., 2000) considers a 2-dimensional regular lattice. Each site is occupied by an agent with a preference $x\_{i}$ sampled from a uniform distribution $U[0,1]$. Agents transfer the information about the quality $q$ of a movie to their neighbors only if $x\_{i}\leq q$. Information percolates through the lattice if $q=q\_{c}=0.593$. -- From a network perspective the percolating cluster can be seen as a random-regular network with $n\_{c}$ nodes and a mean degree that depends on $q\_{c}$. Preserving these quantities of the random-regular network, a true random network can be generated from the $G(n,p)$ model after determining the link probability $p$. I then demonstrate how this random network can be transformed into a threshold network, where agents create links dependent on their $x\_{i}$ values. Assuming a dynamics of the $x\_{i}$ and a mechanism of group formation, I further extend the model toward an adaptive social network model.",
volume = "570",
year = "2021",
arxivid = "2010.06393",
archiveprefix = "ArXiV",
pages = "125687"
}