A model for meme popularity growth in social networking systems based on biological principle and human interest dynamics.
Chaos
; 29(2): 023136, 2019 Feb.
Article
en En
| MEDLINE
| ID: mdl-30823725
ABSTRACT
We analyze five big data sets from a variety of online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors. For example, there is linear growth associated with online recommendation and sharing platforms, a plateaued (or an "S"-shape) type of growth behavior in a web service devoted to helping users to collect bookmarks, and an exponential increase on the largest and most popular microblogging website in China. Does a universal mechanism with a common set of dynamical rules exist, which can explain these empirically observed, distinct growth behaviors? We provide an affirmative answer in this paper. In particular, inspired by biomimicry to take advantage of cell population growth dynamics in microbial ecology, we construct a base growth model for meme popularity in OSNs. We then take into account human factors by incorporating a general model of human interest dynamics into the base model. The final hybrid model contains a small number of free parameters that can be estimated purely from data. We demonstrate that our model is universal in the sense that, with a few parameters estimated from data, it can successfully predict the distinct meme growth dynamics. Our study represents a successful effort to exploit principles in biology to understand online social behaviors by incorporating the traditional microbial growth model into meme popularity. Our model can be used to gain insights into critical issues such as classification, robustness, optimization, and control of OSN systems.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Conducta Social
/
Internet
/
Red Social
/
Medios de Comunicación Sociales
/
Modelos Teóricos
Tipo de estudio:
Prognostic_studies
Aspecto:
Determinantes_sociais_saude
Límite:
Humans
Idioma:
En
Revista:
Chaos
Asunto de la revista:
CIENCIA
Año:
2019
Tipo del documento:
Article
País de afiliación:
Estados Unidos