Resilience denotes the capacity of a system to withstand shocks and its
ability to recover from them. We develop a framework to quantify the resilience
of highly volatile, non-equilibrium social organizations, such as collectives
or collaborating teams. It consists of four steps: (i) delimitation,
i.e., narrowing down the target systems, (ii) conceptualization, .e.,
identifying how to approach social organizations, (iii) formal
representation using a combination of agent-based and network models,
(iv) operationalization, i.e. specifying measures and demonstrating how
they enter the calculation of resilience. Our framework quantifies two
dimensions of resilience, the robustness of social organizations and
their adaptivity, and combines them in a novel resilience measure. It
allows monitoring resilience instantaneously using longitudinal data instead of
an ex-post evaluation.
%0 Generic
%1 schweitzer2022modeling
%A Schweitzer, Frank
%A Andres, Georges
%A Casiraghi, Giona
%A Gote, Christoph
%A Roller, Ramona
%A Scholtes, Ingo
%A Vaccario, Giacomo
%A Zingg, Christian
%D 2022
%K caidas-area-css
%T Modeling social resilience: Questions, answers, open problems
%U http://arxiv.org/abs/2301.00183
%X Resilience denotes the capacity of a system to withstand shocks and its
ability to recover from them. We develop a framework to quantify the resilience
of highly volatile, non-equilibrium social organizations, such as collectives
or collaborating teams. It consists of four steps: (i) delimitation,
i.e., narrowing down the target systems, (ii) conceptualization, .e.,
identifying how to approach social organizations, (iii) formal
representation using a combination of agent-based and network models,
(iv) operationalization, i.e. specifying measures and demonstrating how
they enter the calculation of resilience. Our framework quantifies two
dimensions of resilience, the robustness of social organizations and
their adaptivity, and combines them in a novel resilience measure. It
allows monitoring resilience instantaneously using longitudinal data instead of
an ex-post evaluation.
@misc{schweitzer2022modeling,
abstract = {Resilience denotes the capacity of a system to withstand shocks and its
ability to recover from them. We develop a framework to quantify the resilience
of highly volatile, non-equilibrium social organizations, such as collectives
or collaborating teams. It consists of four steps: (i) \emph{delimitation},
i.e., narrowing down the target systems, (ii) \emph{conceptualization}, .e.,
identifying how to approach social organizations, (iii) formal
\emph{representation} using a combination of agent-based and network models,
(iv) \emph{operationalization}, i.e. specifying measures and demonstrating how
they enter the calculation of resilience. Our framework quantifies two
dimensions of resilience, the \emph{robustness} of social organizations and
their \emph{adaptivity}, and combines them in a novel resilience measure. It
allows monitoring resilience instantaneously using longitudinal data instead of
an ex-post evaluation.},
added-at = {2023-01-23T10:30:12.000+0100},
author = {Schweitzer, Frank and Andres, Georges and Casiraghi, Giona and Gote, Christoph and Roller, Ramona and Scholtes, Ingo and Vaccario, Giacomo and Zingg, Christian},
biburl = {https://www.bibsonomy.org/bibtex/2f3965328803227bfb621f002c73fa32d/ifland},
interhash = {d07343a206d14f853981b8649a6a2b59},
intrahash = {f3965328803227bfb621f002c73fa32d},
keywords = {caidas-area-css},
note = {cite arxiv:2301.00183},
timestamp = {2023-01-23T10:30:12.000+0100},
title = {Modeling social resilience: Questions, answers, open problems},
url = {http://arxiv.org/abs/2301.00183},
year = 2022
}