On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Networks analysis, complexity, and brain function
Complexity - Special issue: Selection, tinkering, and emergence in complex networks
Linked: How Everything Is Connected to Everything Else and What It Means
Linked: How Everything Is Connected to Everything Else and What It Means
Python 3 Reference Manual
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The topic of this study is two-fold and two models are presented. For the first part, I propose a non-linear learning algorithm that takes into account both proximity of opinions and network effects. Agents reach consensus of a final opinion that can be estimated given initial conditions under star and small-world networks. However, when the network structure is scale-free, simulation results show rather chaotic patterns. In the second half of this paper, a two-stage endogenous network formation mechanism is introduced. Opinion closeness is critical in establishing links. Existing neighbors also play an important role in connecting to new neighbors, which, combined with a growing population, contributes to a power-law degree distribution with coefficients that fit empirical findings extremely well. The correlation between opinion and degree is illustrated and formalized as well.