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* (a) Scale-free networks assume a continuous growth of the number of nodes ''N'', compared to random networks which assume a fixed number of nodes. In scale-free networks the degree of the largest hub rises polynomially with the size of the network. Therefore, the degree of a hub can be high in a scale-free network. In random networks the degree of the largest node rises logaritmically (or slower) with N, thus the hub number will be small even in a very large network.

* (a) Scale-free networks assume a continuous growth of the number of nodes ''N'', compared to random networks which assume a fixed number of nodes. In scale-free networks the degree of the largest hub rises polynomially with the size of the network. Therefore, the degree of a hub can be high in a scale-free network. In random networks the degree of the largest node rises logaritmically (or slower) with N, thus the hub number will be small even in a very large network.

*（a）无标度网络假设节点数量''N''保持持续的增长，而随机网络则假设节点数量是固定的。在无标度网络中，最大枢纽的度随着网络规模的增大，呈多项式地上升。因此，在无标度网络中，枢纽的度可以很高。而在随机网络中，最大节点的度随''N''的增大而呈对数式（或更慢）的增大。因此即使在一个非常大的随机网络中，枢纽的数量也会很小。

*（a）无标度网络假设节点数量''N''保持持续的增长，而随机网络则假设节点数量是固定的。在无标度网络中，最大枢纽的度随着网络规模的增大，呈多项式地上升。因此，在无标度网络中，枢纽的度可以很高。而在随机网络中，最大节点的度随''N''的增大而呈对数式（或更慢）的上升。因此即使在一个非常大的随机网络中，枢纽的数量也会很小。

* (b) A new node in a scale-free network has a tendency to link to a node with a higher degree, compared to a new node in a random network which links itself to a random node. This process is called [[preferential attachment]]. The tendency of a new node to link to a node with a high degree ''k'' is characterized by [[Power law|power-law distribution]] (also known as rich-gets-richer process). This idea was introduced by [[Vilfredo Pareto]] and it explained why a small percentage of the population earns most of the money. This process is present in networks as well, for example 80 percent of web links point to 15 percent of webpages. The emergence of scale-free networks is not typical only of networks created by human action, but also of such networks as metabolic networks or illness networks.<ref>Barabási, Albert-László. ''Network Science: The Scale-Free Property''., p. 8.[http://barabasi.com/networksciencebook/content/book_chapter_2.pdf]</ref> This phenomenon may be explained by the example of hubs on the World Wide Web such as Facebook or Google. These webpages are very well known and therefore the tendency of other webpages pointing to them is much higher than linking to random small webpages.

* (b) A new node in a scale-free network has a tendency to link to a node with a higher degree, compared to a new node in a random network which links itself to a random node. This process is called [[preferential attachment]]. The tendency of a new node to link to a node with a high degree ''k'' is characterized by [[Power law|power-law distribution]] (also known as rich-gets-richer process). This idea was introduced by [[Vilfredo Pareto]] and it explained why a small percentage of the population earns most of the money. This process is present in networks as well, for example 80 percent of web links point to 15 percent of webpages. The emergence of scale-free networks is not typical only of networks created by human action, but also of such networks as metabolic networks or illness networks.<ref>Barabási, Albert-László. ''Network Science: The Scale-Free Property''., p. 8.[http://barabasi.com/networksciencebook/content/book_chapter_2.pdf]</ref> This phenomenon may be explained by the example of hubs on the World Wide Web such as Facebook or Google. These webpages are very well known and therefore the tendency of other webpages pointing to them is much higher than linking to random small webpages.