Link-based influence maximization in networks of health promotion professionals.

The influence maximization problem (IMP) as classically formulated is based on the strong assumption that "chosen" nodes always adopt the new product. In this paper we propose a new influence maximization problem, referred to as the "Link-based Influence Maximization Problem" (LI...

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Autores principales:	Maurits H W Oostenbroek, Marco J van der Leij, Quinten A Meertens, Cees G H Diks, Heleen M Wortelboer
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/37a8ff9e1d684dccbdd9df30a09d132a
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spelling	oai:doaj.org-article:37a8ff9e1d684dccbdd9df30a09d132a2021-12-02T20:19:35ZLink-based influence maximization in networks of health promotion professionals.1932-620310.1371/journal.pone.0256604https://doaj.org/article/37a8ff9e1d684dccbdd9df30a09d132a2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0256604https://doaj.org/toc/1932-6203The influence maximization problem (IMP) as classically formulated is based on the strong assumption that "chosen" nodes always adopt the new product. In this paper we propose a new influence maximization problem, referred to as the "Link-based Influence Maximization Problem" (LIM), which differs from IMP in that the decision variable of the spreader has changed from choosing an optimal seed to selecting an optimal node to influence in order to maximize the spread. Based on our proof that LIM is NP-hard with a monotonic increasing and submodular target function, we propose a greedy algorithm, GLIM, for optimizing LIM and use numerical simulation to explore the performance in terms of spread and computation time in different network types. The results indicate that the performance of LIM varies across network types. We illustrate LIM by applying it in the context of a Dutch national health promotion program for prevention of youth obesity within a network of Dutch schools. GLIM is seen to outperform the other methods in all network types at the cost of a higher computation time. These results suggests that GLIM may be utilized to increase the effectiveness of health promotion programs.Maurits H W OostenbroekMarco J van der LeijQuinten A MeertensCees G H DiksHeleen M WortelboerPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0256604 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Maurits H W Oostenbroek Marco J van der Leij Quinten A Meertens Cees G H Diks Heleen M Wortelboer Link-based influence maximization in networks of health promotion professionals.
description	The influence maximization problem (IMP) as classically formulated is based on the strong assumption that "chosen" nodes always adopt the new product. In this paper we propose a new influence maximization problem, referred to as the "Link-based Influence Maximization Problem" (LIM), which differs from IMP in that the decision variable of the spreader has changed from choosing an optimal seed to selecting an optimal node to influence in order to maximize the spread. Based on our proof that LIM is NP-hard with a monotonic increasing and submodular target function, we propose a greedy algorithm, GLIM, for optimizing LIM and use numerical simulation to explore the performance in terms of spread and computation time in different network types. The results indicate that the performance of LIM varies across network types. We illustrate LIM by applying it in the context of a Dutch national health promotion program for prevention of youth obesity within a network of Dutch schools. GLIM is seen to outperform the other methods in all network types at the cost of a higher computation time. These results suggests that GLIM may be utilized to increase the effectiveness of health promotion programs.
format	article
author	Maurits H W Oostenbroek Marco J van der Leij Quinten A Meertens Cees G H Diks Heleen M Wortelboer
author_facet	Maurits H W Oostenbroek Marco J van der Leij Quinten A Meertens Cees G H Diks Heleen M Wortelboer
author_sort	Maurits H W Oostenbroek
title	Link-based influence maximization in networks of health promotion professionals.
title_short	Link-based influence maximization in networks of health promotion professionals.
title_full	Link-based influence maximization in networks of health promotion professionals.
title_fullStr	Link-based influence maximization in networks of health promotion professionals.
title_full_unstemmed	Link-based influence maximization in networks of health promotion professionals.
title_sort	link-based influence maximization in networks of health promotion professionals.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/37a8ff9e1d684dccbdd9df30a09d132a
work_keys_str_mv	AT mauritshwoostenbroek linkbasedinfluencemaximizationinnetworksofhealthpromotionprofessionals AT marcojvanderleij linkbasedinfluencemaximizationinnetworksofhealthpromotionprofessionals AT quintenameertens linkbasedinfluencemaximizationinnetworksofhealthpromotionprofessionals AT ceesghdiks linkbasedinfluencemaximizationinnetworksofhealthpromotionprofessionals AT heleenmwortelboer linkbasedinfluencemaximizationinnetworksofhealthpromotionprofessionals
_version_	1718374158917697536

Link-based influence maximization in networks of health promotion professionals.

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