A Simple Model of Global Cascades on Random Networks¶
Watts, D. J. (2002). A Simple Model of Global Cascades on Random Networks. Proceedings of the National Academy of Sciences, 99(9), 5766-5771.
Cited by¶
7 citations across 7 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Cascade
- The defining commitment is sequential transmission through coupling: each affected element does not merely register the disturbance but becomes a new source of it, re-emitting the perturbation to elements that had not yet been reached.
This sourceThreshold model in which a node flips when the flipped fraction of its neighbors exceeds a threshold and then re-emits to its own neighbors, so small initial shocks can trigger large global cascades; identifies sub-critical vs super-critical regimes set by coupling density and threshold distribution and shows outcome magnitude is decoupled from trigger magnitude.
- The defining commitment is sequential transmission through coupling: each affected element does not merely register the disturbance but becomes a new source of it, re-emitting the perturbation to elements that had not yet been reached.
- Contagion
- Practitioners who recognize the shared structure can import a tested intervention from a foreign domain rather than reinventing it, which is the practical payoff of treating contagion as a single prime rather than as a set of unrelated domain phenomena.
This sourceThreshold model in which each affected node re-emits to its neighbors, so small initial shocks can trigger large global cascades; identifies the sub-critical/super-critical regimes separated by coupling density and threshold distribution, and shows outcome magnitude is decoupled from trigger magnitude.
- Practitioners who recognize the shared structure can import a tested intervention from a foreign domain rather than reinventing it, which is the practical payoff of treating contagion as a single prime rather than as a set of unrelated domain phenomena.
- Herding Behavior
- In political polling and election dynamics, reported poll standings influence voter behavior through bandwagon effects; late-decider studies in U.S. presidential elections repeatedly find this pattern, with voters updating toward perceived frontrunners more than fundamental data would justify.
This sourceThreshold model in which each affected node re-emits to its neighbors, so small initial shocks can trigger large global cascades; identifies the sub-critical/super-critical regimes separated by coupling density and threshold distribution, and shows outcome magnitude is decoupled from trigger magnitude.
- In political polling and election dynamics, reported poll standings influence voter behavior through bandwagon effects; late-decider studies in U.S. presidential elections repeatedly find this pattern, with voters updating toward perceived frontrunners more than fundamental data would justify.
- Information Cascade
- A core function of "information cascade" is to distinguish between genuine information aggregation (many independent signals combining toward accurate consensus) and cascade conformity (early choices hiding information, collapsing diversity into false consensus), a distinction Watts (2002) formalized in his network model of global cascades.
This sourceThreshold model in which each affected node re-emits to its neighbors, so small initial shocks can trigger large global cascades; identifies the sub-critical/super-critical regimes separated by coupling density and threshold distribution, and shows outcome magnitude is decoupled from trigger magnitude.
- A core function of "information cascade" is to distinguish between genuine information aggregation (many independent signals combining toward accurate consensus) and cascade conformity (early choices hiding information, collapsing diversity into false consensus), a distinction Watts (2002) formalized in his network model of global cascades.
- Percolation Threshold
- Granovetter's threshold models of collective behaviour and Watts's cascade models carried the percolation framework — backbone, critical cluster, and all — into social dynamics.
This sourceCarries the percolation framework (critical cluster, giant component) into social cascade dynamics on networks.
- Granovetter's threshold models of collective behaviour and Watts's cascade models carried the percolation framework — backbone, critical cluster, and all — into social dynamics.
- Propagation
- What amplifies the signal, and what dampens it, as Watts (2002) demonstrates by showing that cascade behavior depends on network connectivity rather than the triggering event alone?
This sourceThreshold model in which each affected node re-emits to its neighbors, so small initial shocks can trigger large global cascades; identifies the sub-critical/super-critical regimes separated by coupling density and threshold distribution, and shows outcome magnitude is decoupled from trigger magnitude.
- What amplifies the signal, and what dampens it, as Watts (2002) demonstrates by showing that cascade behavior depends on network connectivity rather than the triggering event alone?
- Systemic Risk
- Recognizing the pattern enables reasoning about contagion paths, critical (too-connected-to-fail) nodes, the difference between robust-yet-fragile architectures, and why adding connections can raise both efficiency and systemic vulnerability simultaneously.
This sourceThreshold model in which each affected node re-emits to its neighbors, so small initial shocks can trigger large global cascades; identifies the sub-critical/super-critical regimes separated by coupling density and threshold distribution, and shows outcome magnitude is decoupled from trigger magnitude.
- Recognizing the pattern enables reasoning about contagion paths, critical (too-connected-to-fail) nodes, the difference between robust-yet-fragile architectures, and why adding connections can raise both efficiency and systemic vulnerability simultaneously.
Verification¶
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