#6269. A Weighted Artificial Bee Colony algorithm for influence maximization

September 2026publication date
Proposal available till 20-05-2025
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Journal’s subject area:
Communication;
Computer Networks and Communications;
Information Systems;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
Social media platforms are increasingly used to convey advertising campaigns for products or services. A key issue is to identify an appropriate set of influencers within a social network, investing resources to get them to adopt a product. Influence maximization is an optimization problem that aims at finding a small set of users that maximize the spread of influence in a social network. In this paper we propose an influence maximization algorithm, named Weighted Artificial Bee Colony (WABC), that is based on a bio-inspired technique for identifying a subset of users which maximizes the spread. The proposed algorithm has been applied to a case study that analyzes the propagation of information among Twitter users during the Constitutional Referendum held in Italy in 20XX. Our analysis is aimed at identifying the main influencers of the yes and no factions, and deriving the main information diffusion strategies of each faction during the political campaign.
Keywords:
Bio-inspired computing; Heuristic algorithms; Influence maximization; Information diffusion; Information spread; Social network analysis

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