Research map / Learning theory and algorithms / Submodular and game algorithms
StructInf: Mining Structural Influence from Social Streams
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use StructInf-S3 sampling instead of exact StructInf-Basic | structural influence mining · Weibo | runtime (hours): 19 -> 1.8 | Helped |
| Use StructInf-S3 sampling instead of exact counting | structural influence mining · Weibo | relative error (%): about 1.0% average error | No clear effect |
| Edge sampling (S2) instead of node sampling (S1) (ablation) | StructInf · Weibo | error vs iterations | Hurt |
| Combine node and edge sampling (S3) instead of S1 or S2 alone (ablation) | StructInf · Weibo | sensitivity to parameters | Helped |
| Increase time delay tau beyond 25 hours (ablation) | structural influence of C1 · Weibo | influence probability | No clear effect |
| Add weak structural influence patterns as features to basic features and active neighbor count (ablation) | logistic regression retweet predictor · Weibo retweet prediction | F1: +1.1% | Helped |
| Add strong patterns upon moderate patterns (ablation) | logistic regression retweet predictor · Weibo retweet prediction | F1: +1.73% | Helped |
| Add moderate patterns (ablation) | logistic regression retweet predictor · Weibo retweet prediction | F1 | No clear effect |
Closest papers by meaning
- Link Prediction With Personalized Social Influence (AAAI 2018 · similarity 0.86)
- The Importance of Communities for Learning to Influence (NeurIPS 2017 · similarity 0.86)
- DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation (AAAI 2025 · similarity 0.84)
- Revisiting Link Prediction: a data perspective (ICLR 2024 · similarity 0.82)
- Adversarial Socialbots Modeling Based on Structural Information Principles (AAAI 2024 · similarity 0.82)
- REM: A Scalable Reinforced Multi-Expert Framework for Multiplex Influence Maximization (AAAI 2025 · similarity 0.82)
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