8 citations · 12 across the 13 of their papers we have counts for
6 papers · 1 filter
Group-Harmonic and Group-Closeness Maximization -- Approximation and Engineering
Eugenio Angriman, Ruben Becker, Gianlorenzo D'Angelo +3
Centrality measures characterize important nodes in networks. Efficiently computing such nodes has received a lot of attention. When considering the generalization of computing cen…
Fairness in Influence Maximization through Randomization
Ruben Becker, Gianlorenzo D'Angelo, Sajjad Ghobadi +1
The influence maximization paradigm has been used by researchers in various fields in order to study how information spreads in social networks. While previously the attention was…
Improved Approximation Factor for Adaptive Influence Maximization via Simple Greedy Strategies
Gianlorenzo D'Angelo, Debashmita Poddar, Cosimo Vinci
In the adaptive influence maximization problem, we are given a social network and a budget , and we iteratively select nodes, called seeds, in order to maximize the expected…
Better Bounds on the Adaptivity Gap of Influence Maximization under Full-adoption Feedback
Gianlorenzo D'Angelo, Debashmita Poddar, Cosimo Vinci
In the influence maximization (IM) problem, we are given a social network and a budget , and we look for a set of nodes in the network, called seeds, that maximize the expec…
Multi-Winner Election Control via Social Influence
Mohammad Abouei Mehrizi, Gianlorenzo D'Angelo
In an election, we are given a set of voters, each having a preference list over a set of candidates, that are distributed on a social network. We consider a scenario where voters…
Maximizing Influence-based Group Shapley Centrality
Ruben Becker, Gianlorenzo D'Angelo, Hugo Gilbert
One key problem in network analysis is the so-called influence maximization problem, which consists in finding a set of at most seed users, in a social network, maximizing…