Networks with a community (or modular) structure underlie many social and biological phenomena. In such a network individuals tend to form sparsely linked local communities, each having dense internal connections. We investigate the dynamics of information propagation on modular networks by using a three-state epidemic model with a unit spreading rate (i.e., the probability for a susceptible individual to be "infected" with the information is one). We find a surprising, resonancelike phenomenon: the information lifetime on the network can be maximized by the number of modules. The result can be useful for optimizing or controlling information spread on social or biological networks.
|Original language||English (US)|
|Journal||Physical Review E - Statistical, Nonlinear, and Soft Matter Physics|
|State||Published - Jan 1 2006|
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Statistics and Probability
- Condensed Matter Physics