Blog Acadêmico do Caio

 A large  undirected graph, with no self-loops or multi-links, is analyzed. It exhibits a scale-free degree distribution P(k) = k^y with an exponent y=2.5. Empirical measurement yields a degree correlation coefficient r = -0.15. A plot of the average nearest-neighbor degree shows relatively independency of k for small k, but begins to decay for nodes with k > k_s. What is the most precise classification of this network's degree correlations? A)  The network is intrinsically disassortative B)  The network exhibits structural disassortativity, a phenomenon caused by y < 3  exponent and the netweork's nature. C)  The network is neutral, as   average nearest-neighbor degree  is independent of k  for most nodes and e  is close to 0 D) The network is assortative, but the measurement is skewed by the high variance of high-degree node E)  None of the above Original idea: Caio Rhoden

  Analyze the following statements about the mechanisms and consequences of the Barabási-Albert (BA) model and its derivatives. I. In the standard BA model, the degree distribution exponent (γ) converges to γ=3. This value is a fundamental property of the model, being independent of the parameter m   II. The 'first-mover advantage' is an absolute principle in the BA model, guaranteeing that the initial nodes in the network will invariably become the hubs with the highest degree, since the time spent in the network is the sole determining factor for the accumulation of connections. III. Preferential attachment, by itself, is a sufficient mechanism to generate a scale-free network with a power-law degree distribution, even in a network with a fixed number of nodes. IV. In models with non-linear preferential attachment, where the probability of attachment scales with the degree as k α , an exponent α > 1  results in a more 'democratic' network, where the degree diff...