On the Group-Fairness-Aware Influence Maximization in Social Networks

The goal of influence maximization (IM) is to find a set of k nodes that maximize their influence spread over a social network. IM is a widely used model for information propagation in social networks. Although IM has been widely investigated in recent years, the fair propagation of information is...

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Veröffentlicht in:	IEEE transactions on computational social systems 2023-12, Vol.10 (6), p.3406-3414
Hauptverfasser:	Razaghi, Behnam, Roayaei, Mehdy, Charkari, Nasrollah Moghadam
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Costs Fairness in influence maximization (IM) gray wolf optimizer (GWO) group fairness Heuristic methods Information dissemination Mathematical models Maximization Measurement Metaheuristics Multiple objective analysis Optimization Propagation Resource management Social networking (online) Social networks Time factors
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