Research map / Learning theory and algorithms / Submodular and game algorithms
Minimizing Polarization and Disagreement in Social Networks via Link Recommendation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use FastGreedy approximation instead of exact SpGreedy | edge recommendation for P-D index · large networks (k=50) | running time: 319.86 -> 101.95 s on CondMat | Helped |
| use FastGreedy approximation instead of exact SpGreedy | edge recommendation for P-D index · Reality (k=50) | Delta I(G) ratio: -5.7861 -> -5.7183 | No clear effect |
| use FastGreedy on small network where exact is cheap | edge recommendation · GrQc (k=50) | running time: 7.83 -> 11.13 s | Hurt |
| greedy algorithms versus exhaustive optimum on small networks | SpGreedy and FastGreedy · Karate, Dolphins, Netscience, Diseasom | Delta I(G) | No clear effect |
| greedy algorithms versus Random edge selection | SpGreedy and FastGreedy · small networks | Delta I(G) | Helped |
| FastGreedy versus degree and betweenness heuristics | edge recommendation · Yeast, GridWorm, Erdos992, Reality | Delta I(G) | Helped |
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