Role-Aware Information Spread in Online Social Networks

Understanding the complex process of information spread in online social networks (OSNs) enables the efficient maximization/minimization of the spread of useful/harmful information. Users assume various roles based on their behaviors while engaging with information in these OSNs. Recent reviews on i...

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Autores principales:	Alon Bartal, Kathleen M. Jagodnik
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	global information spread information diffusion local information spread non-viral information spread online social networks role-aware analysis Science Q Astrophysics QB460-466 Physics QC1-999
Acceso en línea:	https://doaj.org/article/a9ecffd21aaa4b8f9366dff163965557
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spelling	oai:doaj.org-article:a9ecffd21aaa4b8f9366dff1639655572021-11-25T17:30:51ZRole-Aware Information Spread in Online Social Networks10.3390/e231115421099-4300https://doaj.org/article/a9ecffd21aaa4b8f9366dff1639655572021-11-01T00:00:00Zhttps://www.mdpi.com/1099-4300/23/11/1542https://doaj.org/toc/1099-4300Understanding the complex process of information spread in online social networks (OSNs) enables the efficient maximization/minimization of the spread of useful/harmful information. Users assume various roles based on their behaviors while engaging with information in these OSNs. Recent reviews on information spread in OSNs have focused on algorithms and challenges for modeling the local node-to-node cascading paths of viral information. However, they neglected to analyze non-viral information with low reach size that can also spread globally beyond OSN edges (links) via non-neighbors through, for example, pushed information via content recommendation algorithms. Previous reviews have also not fully considered user roles in the spread of information. To address these gaps, we: (i) provide a comprehensive survey of the latest studies on role-aware information spread in OSNs, also addressing the different temporal spreading patterns of viral and non-viral information; (ii) survey modeling approaches that consider structural, non-structural, and hybrid features, and provide a taxonomy of these approaches; (iii) review software platforms for the analysis and visualization of role-aware information spread in OSNs; and (iv) describe how information spread models enable useful applications in OSNs such as detecting influential users. We conclude by highlighting future research directions for studying information spread in OSNs, accounting for dynamic user roles.Alon BartalKathleen M. JagodnikMDPI AGarticleglobal information spreadinformation diffusionlocal information spreadnon-viral information spreadonline social networksrole-aware analysisScienceQAstrophysicsQB460-466PhysicsQC1-999ENEntropy, Vol 23, Iss 1542, p 1542 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	global information spread information diffusion local information spread non-viral information spread online social networks role-aware analysis Science Q Astrophysics QB460-466 Physics QC1-999
spellingShingle	global information spread information diffusion local information spread non-viral information spread online social networks role-aware analysis Science Q Astrophysics QB460-466 Physics QC1-999 Alon Bartal Kathleen M. Jagodnik Role-Aware Information Spread in Online Social Networks
description	Understanding the complex process of information spread in online social networks (OSNs) enables the efficient maximization/minimization of the spread of useful/harmful information. Users assume various roles based on their behaviors while engaging with information in these OSNs. Recent reviews on information spread in OSNs have focused on algorithms and challenges for modeling the local node-to-node cascading paths of viral information. However, they neglected to analyze non-viral information with low reach size that can also spread globally beyond OSN edges (links) via non-neighbors through, for example, pushed information via content recommendation algorithms. Previous reviews have also not fully considered user roles in the spread of information. To address these gaps, we: (i) provide a comprehensive survey of the latest studies on role-aware information spread in OSNs, also addressing the different temporal spreading patterns of viral and non-viral information; (ii) survey modeling approaches that consider structural, non-structural, and hybrid features, and provide a taxonomy of these approaches; (iii) review software platforms for the analysis and visualization of role-aware information spread in OSNs; and (iv) describe how information spread models enable useful applications in OSNs such as detecting influential users. We conclude by highlighting future research directions for studying information spread in OSNs, accounting for dynamic user roles.
format	article
author	Alon Bartal Kathleen M. Jagodnik
author_facet	Alon Bartal Kathleen M. Jagodnik
author_sort	Alon Bartal
title	Role-Aware Information Spread in Online Social Networks
title_short	Role-Aware Information Spread in Online Social Networks
title_full	Role-Aware Information Spread in Online Social Networks
title_fullStr	Role-Aware Information Spread in Online Social Networks
title_full_unstemmed	Role-Aware Information Spread in Online Social Networks
title_sort	role-aware information spread in online social networks
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/a9ecffd21aaa4b8f9366dff163965557
work_keys_str_mv	AT alonbartal roleawareinformationspreadinonlinesocialnetworks AT kathleenmjagodnik roleawareinformationspreadinonlinesocialnetworks
_version_	1718412244437434368

Role-Aware Information Spread in Online Social Networks

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