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Stigmergy-based influence maximization in social networks

Citation

Li, W and Bai, Q and Jiang, C and Zhang, M, Stigmergy-based influence maximization in social networks, Proceedings of the 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2016). Lecture Notes in Computer Science, volume 9810, 22-26 August 2016, Phuket, Thailand, pp. 750-762. ISBN 9783319429106 (2016) [Refereed Conference Paper]


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Copyright 2016 Springer

DOI: doi:10.1007/978-3-319-42911-3_63

Abstract

Influence maximization is an important research topic which has been extensively studied in various fields. In this paper, a stigmergybased approach has been proposed to tackle the influence maximization problem. We modelled the influence propagation process as ant’s crawling behaviours, and their communications rely on a kind of biological chemicals, i.e., pheromone. The amount of the pheromone allocation is concerning the factors of influence propagation in the social network. The model is capable of analysing influential relationships in a social network in decentralized manners and identifying the influential users more efficiently than traditional seed selection algorithms.

Item Details

Item Type:Refereed Conference Paper
Keywords:influence maximization, ant algorithm, stigmergy
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Intelligent robotics
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:140685
Year Published:2016
Web of Science® Times Cited:5
Deposited By:Information and Communication Technology
Deposited On:2020-09-01
Last Modified:2020-11-09
Downloads:0

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