Group relations, resilience and the I Ching

Schweitzer, Frank

doi:10.1016/j.physa.2022.127630

Cited by 6 publications

(4 citation statements)

References 46 publications

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“…To formalize the relations postulated, we propose quantifying resilience as the convex combination of R and A ^ , as proposed in (Schweitzer, 2022) and shown in Figure 3b:…”

Section: A New Resilience Measurementioning

confidence: 99%

Struggling With Change: The Fragile Resilience of Collectives

Schweitzer,

Zingg,

Casiraghi

2023

Perspect Psychol Sci

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Collectives form nonequilibrium social structures characterized by volatile dynamics. Individuals join or leave. Social relations change quickly. Therefore, unlike engineered or ecological systems, a resilient reference state cannot be defined. We propose a novel resilience measure combining two dimensions: robustness and adaptivity. We demonstrate how they can be quantified using data from a software-developer collective. Our analysis reveals a resilience life cycle (i.e., stages of increasing resilience are followed by stages of decreasing resilience). We explain the reasons for these observed dynamics and provide a formal model to reproduce them. The resilience life cycle allows distinguishing between short-term resilience, given by a sequence of resilient states, and long-term resilience, which requires collectives to survive through different cycles.

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“…To formalize the relations postulated, we propose quantifying resilience as the convex combination of R and A ^ , as proposed in (Schweitzer, 2022) and shown in Figure 3b:…”

Section: A New Resilience Measurementioning

confidence: 99%

Struggling With Change: The Fragile Resilience of Collectives

Schweitzer,

Zingg,

Casiraghi

2023

Perspect Psychol Sci

Self Cite

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“…Because there is no general solution, we resort to some guiding examples. In the simplest case, importance is defined in the hierarchical structure of a team [148]. There are also ways to determine hierarchies based on interaction patterns.…”

Section: Quantifying Agent Propertiesmentioning

confidence: 99%

“…Correcting for these shortcomings is an open discussion. As a possible alternative we have proposed a new weighted balance measure T ijk [143,148] that takes into account not only the signs and the weights of the signed relations, but also the impact of the agents involved in the triad. To determine the structural balance of the whole collective, we take the arithmetic mean, ⟨T ⟩ = ∑ T ijk N t , where N t = T ijk is the total number of triads in the network.…”

Section: Structural Robustnessmentioning

confidence: 99%

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Modeling Social Resilience: Questions, Answers, Open Problems

Schweitzer

Andres

Casiraghi

et al. 2022

Advs. Complex Syst.

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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, nonequilibrium social organizations, such as collectives or collaborating teams. It consists of four steps: (i) delimitation, i.e., narrowing down the target systems, (ii) conceptualization, i.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.

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Multidimensional attributes expose Heider balance dynamics to measurements

Linczuk,

Górski,

Szymanski

et al. 2023

Sci Rep

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Most of studied social interactions arise from dyadic relations. An exception is Heider Balance Theory that postulates the existence of triad dynamics, which however has been elusive to observe. Here, we discover a sufficient condition for the Heider dynamics observability: assigning the edge signs according to multiple opinions of connected agents. Using longitudinal records of university student mutual contacts and opinions, we create a coevolving network on which we introduce models of student interactions. These models account for: multiple topics of individual student opinions, influence of such opinions on dyadic relations, and influence of triadic relations on opinions. We show that the triadic influence is empirically measurable for static and dynamic observables when signs of edges are defined by multidimensional differences between opinions on all topics. Yet, when these signs are defined by a difference between opinions on each topic separately, the triadic interactions’ influence is indistinguishable from noise.

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Group relations, resilience and the I Ching

Cited by 6 publications

References 46 publications

Struggling With Change: The Fragile Resilience of Collectives

Struggling With Change: The Fragile Resilience of Collectives

Modeling Social Resilience: Questions, Answers, Open Problems

Multidimensional attributes expose Heider balance dynamics to measurements

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