The University of Southampton
University of Southampton Institutional Repository

Identifying the influential spreaders in multilayer interactions of online social networks

Identifying the influential spreaders in multilayer interactions of online social networks
Identifying the influential spreaders in multilayer interactions of online social networks
Online social networks (OSNs) portray a multi-layer of interactions through which users become a friend, information is propagated, ideas are shared, and interaction is constructed within an OSN. Identifying the most influential spreaders in a network is a significant step towards improving the use of existing resources to speed up the spread of information for application such as viral marketing or hindering the spread of information for application like virus blocking and rumor restraint. Users communications facilitated by OSNs could confront the temporal and spatial limitations of traditional communications in an exceptional way, thereby presenting new layers of social interactions, which coincides and collaborates with current interaction layers to redefine the multiplex OSN. In this paper, the effects of different topological network structure on influential spreaders identification are investigated. The results analysis concluded that improving the accuracy of influential spreaders identification in OSNs is not only by improving identification algorithms but also by developing a network topology that represents the information diffusion well. Moreover, in this paper a topological representation for an OSN is proposed which takes into accounts both multilayers interactions as well as overlaying links as weight. The measurement results are found to be more reliable when the identification algorithms are applied to proposed topological representation compared when these algorithms are applied to single layer representations.
online social networks, complex network, multilayer interaction, influential spreaders
1064-1246
1-19
Al-garadi, Mohammed Ali
51bdd2aa-c73b-4702-abf3-5502990561cd
Varathan, Kasturi Dewi
0024a3ff-5ec9-4828-96af-dc8d33896dc6
Ravana, Sri Devi
80fb68d5-615a-4a39-9890-f7268cb9cfb4
Ahmed, Ejaz
9c02b4c5-d0e4-4c01-8598-77c6b27aea4b
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Al-garadi, Mohammed Ali
51bdd2aa-c73b-4702-abf3-5502990561cd
Varathan, Kasturi Dewi
0024a3ff-5ec9-4828-96af-dc8d33896dc6
Ravana, Sri Devi
80fb68d5-615a-4a39-9890-f7268cb9cfb4
Ahmed, Ejaz
9c02b4c5-d0e4-4c01-8598-77c6b27aea4b
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4

Al-garadi, Mohammed Ali, Varathan, Kasturi Dewi, Ravana, Sri Devi, Ahmed, Ejaz and Chang, Victor (2016) Identifying the influential spreaders in multilayer interactions of online social networks. [in special issue: Multimedia in Technology Enhanced Learning] Journal of Intelligent & Fuzzy Systems, 1-19. (In Press)

Record type: Article

Abstract

Online social networks (OSNs) portray a multi-layer of interactions through which users become a friend, information is propagated, ideas are shared, and interaction is constructed within an OSN. Identifying the most influential spreaders in a network is a significant step towards improving the use of existing resources to speed up the spread of information for application such as viral marketing or hindering the spread of information for application like virus blocking and rumor restraint. Users communications facilitated by OSNs could confront the temporal and spatial limitations of traditional communications in an exceptional way, thereby presenting new layers of social interactions, which coincides and collaborates with current interaction layers to redefine the multiplex OSN. In this paper, the effects of different topological network structure on influential spreaders identification are investigated. The results analysis concluded that improving the accuracy of influential spreaders identification in OSNs is not only by improving identification algorithms but also by developing a network topology that represents the information diffusion well. Moreover, in this paper a topological representation for an OSN is proposed which takes into accounts both multilayers interactions as well as overlaying links as weight. The measurement results are found to be more reliable when the identification algorithms are applied to proposed topological representation compared when these algorithms are applied to single layer representations.

Text
JIFS_social_networks_accepted.pdf - Accepted Manuscript
Download (1MB)

More information

Accepted/In Press date: 26 May 2016
Keywords: online social networks, complex network, multilayer interaction, influential spreaders
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 395586
URI: http://eprints.soton.ac.uk/id/eprint/395586
ISSN: 1064-1246
PURE UUID: 144fc9a4-1e8a-4922-8a7e-2a795416be9c

Catalogue record

Date deposited: 27 May 2016 13:01
Last modified: 18 Jul 2020 04:01

Export record

Contributors

Author: Mohammed Ali Al-garadi
Author: Kasturi Dewi Varathan
Author: Sri Devi Ravana
Author: Ejaz Ahmed
Author: Victor Chang

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×