Abstract
Complex networks are characterized based on a newly proposed parameter, " degree of diffusion α" It defines the ratio of information adopters to non-adopters within a diffusion process over consecutive penetration depths. Furthermore, the perfectness of a social network is evaluated by exploring different variations of α such as the reverse diffusion (αreverse) and the random-kill-diffusion (RKD) processes. The analysis of αreverse and RKD processes shows information diffusion irreversibility in small-world and scale-free but not in random networks. It also shows that random networks are more stable toward attacks, resulting a complete information diffusion process over the entire network. Finally, a real Complex network example, represented as a " virtual friendship network" was analyzed and found to share properties of both random and small-world networks. Therefore, it is characterized to be somewhere between random and small-world network models or in other words, it is a randomized small-world network model. © 2011 Elsevier B.V. © 2011 Elsevier B.V., All rights reserved.
| Original language | American English |
|---|---|
| Pages (from-to) | 198-206 |
| Number of pages | 9 |
| Journal | Journal of Computational Science |
| Volume | 2 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2011 |
| Externally published | Yes |
Funding Agency
- Kuwait Foundation for the Advancement of Sciences