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

Gleeson, James P.; O', Kevin P.; Sullivan, ; Baños, 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:

• Social Networks
• Multiplex (3rd period)

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