Effects of network structure, competition and memory time on social spreading phenomena

Gleeson, James P. ; O’Sullivan, Kevin P. ; Baños, Raquel A. ; Moreno, Yamir (Universidad de Zaragoza)

Resumen: Online social media has greatly affected the way in which we communicate with each other. However, little is known about what fundamental mechanisms drive dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior that is analytically tractable and that can reproduce several characteristics of empirical micro-blogging data on hashtag usage, such as (time-dependent) heavy-tailed distributions of meme popularity. The presented framework constitutes a null model for social spreading phenomena that, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity structure of the social network.

Idioma: Inglés

DOI: 10.1103/PhysRevX.6.021019

Año: 2016

Publicado en: Physical review. X 6, 2 (2016), 021019 [22 pp]
ISSN: 2160-3308

Factor impacto JCR: 12.789 (2016)

Categ. JCR: PHYSICS, MULTIDISCIPLINARY rank: 5 / 79 = 0.063 (2016) - Q1 - T1

Factor impacto SCIMAGO: 7.434 - Physics and Astronomy (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/FENOL-GROUP
Financiación: info:eu-repo/grantAgreement/EC/FP7/317532/EU/Foundational Research on MULTIlevel comPLEX networks and systems/MULTIPLEX
Financiación: info:eu-repo/grantAgreement/EC/FP7/317614/EU/Mathematical framework for multiplex networks/PLEXMATH
Financiación: info:eu-repo/grantAgreement/ES/MINECO/FIS2011-25167

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Física Teórica (Dpto. Física Teórica)