Complete the sentences with RN or SFN in the following statements, When we compare random networks (RN) and scale-free networks (SFN).
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I) In ___, most nodes have the same number of links.
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II) In ___, many nodes with only a few links.
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III) In ___, there are A few hubs with a huge number of links.
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IV) In ___, there are Not highly connected nodes.
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V) In ___, the size of the largest node grows logarithmically or slower with N, implying that hubs will be tiny even in a very large ___.
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VI) In__ the size of the hubs grows polynomially with network size; hence they can grow quite large in ___.
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VII) A ___ follows a Poisson distribution, quite similar to a bell curve.
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VIII) In __ the distribution, most nodes have only a few links. A few highly connected hubs hold together these numerous small nodes.
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A) RN: I, II,IV, VI,VII and SFN:III, V, VIII
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B) RN: II, III,IV, Vand SFN:I,V, VI,VII, VIII
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C) RN: I, IV V,VII and SFN:II,III, VI, VIII
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D) RN: I, IV VI,VII and SFN:II,III, V, VIII
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E) None of the above.
Original idea by: Rolan Alexander Valle Rey Sánchez.
Nice question, but it has a few problems. For instance, in (I), it is not true to say that most nodes will have degree equal top the average. If you look at a plot of a binomial distribution, you wil, see that the max value of p_k is usually below 50%. In (III) and (IV) there are upper case letters in the phrase, where there shouldn't be. In (VI), the notion of highly connected is not sufficiently precise for a question. We may say it informally, but in a question like this, we need a more precise definition. For instance, is a node with degree above average highly connected? Is a node with degree one standard deviation above the average highly connected? Is a node with degree higher than 1.5 times the average highly connected? In (VII), are you saying that all Poisson distributions look like Bell curves? I have doubts about that. In summary, you need to be more careful in your statements.
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