Research map / Probabilistic and scientific modeling / Dynamical systems
Correlated Cascades: Compete or Cooperate
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Model cascades jointly with a nonlinear softmax mark function instead of treating them as independent | Correlated Cascade (CC) · Twitter URL dataset | AvgPredLogLik | Helped |
| Model cascades jointly with a nonlinear softmax mark function instead of treating them as independent | Correlated Cascade (CC) · Twitter music dataset | AvgPredLogLik | Helped |
| Use the competing-products model | Twitter URL dataset · Twitter URL dataset | AvgPredLogLik | Hurt |
| Use the competing-products model | Twitter music dataset · Twitter music dataset | AvgPredLogLik | Hurt |
| Generate test events with the correlated cascade model rather than the alternatives | Correlated Cascade (CC) · Twitter URL and music datasets | Pearson correlation | Helped |
| Generate test events with the correlated cascade model rather than the alternatives | Correlated Cascade (CC) · Twitter URL and music datasets | inverse ℓ1 distance | Helped |
| Replace the exponential softmax mark with the linear mark (ablation) | Correlated Cascade (CC) · Synthetic correlated-cascade incentivization experiment | cross-cascade response to incentivization | Hurt |
| Increase the softmax parameter β toward the highly competitive setting (ablation) | Correlated Cascade (CC) · Synthetic correlated-cascade incentivization experiment | product 3 market share | Helped |
| Set β to the cooperative setting (ablation) | Correlated Cascade (CC) · Synthetic correlated-cascade incentivization experiment | similarity of product intensities after incentivization | Helped |
| Train with more events | Correlated Cascade (CC) · Synthetic data | parameter recovery accuracy | Helped |
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