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Modelling multiple influences diffusion in on-line social networks

Citation

Li, W and Zhang, M and Bai, Q and Nguyen, TD, Modelling multiple influences diffusion in on-line social networks, Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018), 10-15 July 2018, Stockholm, Sweden, pp. 1053-1061. ISBN 9781510868083 (2018) [Refereed Conference Paper]

Copyright Statement

Copyright 2018 8 International Foundation for Autonomous Agents and Multiagent Systems

Official URL: http://ifaamas.org/Proceedings/aamas2018/forms/con...

Abstract

In on-line social networks, innovations in the presence of one or more influences disseminate through the topological structure of the networks rapidly. In reality, various influences normally coexist in the same context and have subtle relations, such as supportive, contradictory and competitive relations, affecting the users' decisions of adopting any innovations. Therefore, modelling diffusion process of multiple influences is an important, yet challenging research question. By employing the agent-based modelling, in this paper, a distributed approach has been proposed to model the diffusion process of multiple influences in social networks. The proposed model has been applied in the undesirable influence minimisation problem, where the time series is taken into consideration. The experimental results show our model can be utilised to minimise the adverse impact of a certain influence by injecting other influences. Furthermore, the proposed model also sheds light on understanding, investigating and analysing multiple influences in social networks.

Item Details

Item Type:Refereed Conference Paper
Keywords:multiple influences, agent-based modelling, influence diffusion, influence minimisation
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:140676
Year Published:2018
Deposited By:Information and Communication Technology
Deposited On:2020-09-01
Last Modified:2020-10-28
Downloads:0

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