Consider a Barabási-Albert network with parameter m=2. A node was introduced at time . At a later time , this node has degree . What is the expected average clustering coefficient of the network at time ?
Let G be an undirected, unweighted network without self-loops and with N nodes. For a given node i , let N i denote the number of neighbors of i . Which of the following expressions correctly represents the denominator of the clustering coefficient for node i , given that the nominator L i represents the actual number of connections between the N i neighbors? ( N i (N i − 1) ) / 2 N i 2 ( N i (N i + 1) ) / 2 N i (N i − 1) None of the above Original idea by: Yan Prada.
About the differences between random networks and real networks, consider the following statements: I. In both real and random networks, the average clustering coefficient depends on N N . II. Real networks often exhibit heavy-tailed degree distributions, while random networks have an approximately Poisson degree distribution. III. The average path length in random networks is of the order of log n \log n , while in many real networks it grows faster. IV. Real networks and random networks have identical critical regimes, since both depend only on the average degree. Which statements are correct? a) I and II b) II and IV c) I, III and IV d) II, III and IV e) None of the above Original idea by: Yan Prada.
Boa questão. Fico com ela. Mudei um pouco.
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