Effects of Network Structure, Competition and Memory Time on Social Spreading Phenomena

Gleeson, James P.; O', Kevin P.; Sullivan, ; BaƱos, Raquel A.; Moreno, Yamir
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.
Research areas:
Year:
2016
Type of Publication:
Article
Keywords:
complex systems
Journal:
Physical Review X
Volume:
6
Number:
2
Pages:
021019
ISSN:
2160-3308
DOI:
10.1103/PhysRevX.6.021019
Hits: 815

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