We define three metrics of the group information power (social capital) in a network based on effective resistance (spectral graph theory). We propose also three metrics of social capital unfairness (structural group unfairness) and a heuristic to mitigate it.
FairShap, i.e. Fair Shapley Values, is a family of data valuation functions for Algorithmic Fairness based on Game Theory which can be used as a novel, interpretable, pre-processing and model-agnostic (re-weighting) method for fair algorithmic decision-making.
Theoretical and empirical framework to analyze and perform graph rewiring in a principled way. Also, proposal of calulation of Commute Times (resistance) in a GNN layer and Bottleneck minimizarion using Spectral gradients.
Understanding and measuring the scientific structure of the computer Science field in Spain.
Graph statistical analysis to unveil the informal structure of the knowledge area of business organization in Spain using TESEO database.
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