Diffusion/Contagion Processes on Social Networks

Autor/inn/en	Valente, Thomas W.; Vega Yon, George G.
Titel	Diffusion/Contagion Processes on Social Networks
Quelle	In: Health Education & Behavior, 47 (2020) 2, S.235-248 (14 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Valente, Thomas W.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1090-1981
DOI	10.1177/1090198120901497
Schlagwörter	Communication (Thought Transfer); Innovation; Communicable Diseases; Social Networks; Models; Adoption (Ideas) + Suchen Sie Ihr Suchwort? Communication; thought; Kommunikation; Gedanke; Contagious disease; Contagious diseases; Communicable disease; Infektionskrankheit; Social network; Soziales Netzwerk; Analogiemodell; Ideas; Ideenfindung
Abstract	This study models how new ideas, practices, or diseases spread within and between communities, the diffusion of innovations or contagion. Several factors affect diffusion such as the characteristics of the initial adopters, the seeds; the structure of the network over which diffusion occurs; and the shape of the threshold distribution, which is the proportion of prior adopting peers needed for the focal individual to adopt. In this study, seven seeding conditions are modeled: (1) three opinion leadership indicators, (2) two bridging measures, (3) marginally positioned seeds, and (4) randomly selected seeds for comparison. Three network structures are modeled: (1) random, (2) small-world, and (3) scale-free. Four threshold distributions are modeled: (1) normal; (2) uniform; (3) beta 7,14; and (4) beta 1,2; all of which have a mean threshold of 33%, with different variances. The results show that seeding with nodes high on in-degree centrality and/or inverse constraint has faster and more widespread diffusion. Random networks had faster and higher prevalence of diffusion than scale-free ones, but not different from small-world ones. Compared with the normal threshold distribution, the uniform one had faster diffusion and the beta 7,14 distribution had slower diffusion. Most significantly, the threshold distribution standard deviation was associated with rate and prevalence such that higher threshold standard deviations accelerated diffusion and increased prevalence. These results underscore factors that health educators and public health advocates should consider when developing interventions or trying to understand the potential for behavior change. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01