What does "going viral" on the internet really mean, and why does it happen so quickly?
“一夜爆红”在网络世界意味着什么？为什么可以如此快速地发生呢？
Why is a financial institution too big to fail?
为什么金融机构有着举足轻重的地位？
How does a virus in Africa end up in the United States in a matter of hours?
是什么让一种源起于非洲的病毒，短短几个小时内就能登陆美国？
Why are Facebook and Google such powerful companies at creating global connections?
为什么脸书和谷歌在连接全球上起着至关重要的作用？
Well, in a word: networks. But what are networks?
答案就是：“网络”。但是“网络”这个词又是什么意思呢？
Everyone knows about their social network,
大家都知道社交网络，
but there are all different kinds of networks you probably haven't thought about.
但是除此之外，还有许多种网络你或许从来没有意识到。
Networks are collections of links which combine by specific rules and behaviors if they are alive.
网络是链接的集合，它们按照一定的规矩和行动连接起来，就好像有生命的一样。
We say that networks are alive because they are in constant change.
我们之所以说网络像是有生命一样，是因为他们始终处于变化之中。
Over time, the connections within a network migrate and concentrate in new places, forming evolving structures.
随着时间的推移，网络中的各种连接点不断的移动并聚集在新的地方，形成新的结构。
How the evolution and concentration of constantly changing connections occurs
研究这些连接点们是如何不停地变换、进化、聚合，
is the subject of a whole discipline called network theory.
是一门学科的主题，这门学科就叫：网络理论。
We can think of networks as neighborhoods. Neighborhoods are defined by maps.
我们可以把网络理解为社区。社区由地图来标记区分。
A Google map demonstrates the relationship between locations in exactly the same fashion a network connects hubs and nodes,
谷歌地图用来界定两地之间距离的方法，和网络连接中心信息点与节点的方法一模一样，
using streets as links to connect neighborhoods.
那就是通过街道来连接两个社区。

The reason a network can expand and evolve so quickly is based upon a mathematical concept called power functions.
网络可以迅速延伸和发展的原因在于，它是基于一个叫做幂函数的数学概念。
A power function is a mathematical amplification mechanism,
幂函数是一个数理增长机制，
which over specific and very small ranges, accelerates changes logarithmically.
一个很小的基数在幂函数里可以呈对数增长。
That is, a very small change in one parameter produces a huge change in another over a very specific range of values.
这就意味着，一个参数的一点点变化，就可以导致另一个数值出现巨大的变化。
An example of how network structure emerges is the algorithm used by Google.
网络结构是如何形成的一个例子，就是谷歌所运用的算法。
As the number of links around a search term, say "friends", increases,
比方说，“朋友”这个关键词的链接增多了，
connections begin to form among millions of different searches using the term "friend".
数以百万次的对“朋友”一词的搜索，就使得围绕着这个关键词的联结点产生了。
What Google has cleverly accomplished is a real-time mathematical model
谷歌所完美实现的是一个实时数理模型，
for how to predict the emergence of growing connections among billions of search terms.
这个模型从千万个搜索词中预测到了联结点们的出现。
The algorithm Google derived collects the number of references to any search object.
Google的算法会搜集任何搜寻对象被引用的次数。
As references to a search object increase, the number of links also increases, creating a node.
随着引用次数的增加，链接的数目也会增加，形成节点。
As the node increases in size, it eventually becomes a hub, which links to many nodes.
而当节点形成一定规模的时候，就会形成把每一个小节点联系起来的信息中心点。
Networks will continue to emerge as new ways of connecting and creating neighborhoods are defined.
网络会不断的发展，因为连接和创造“社区”的方法在不断更新。
Perhaps you can begin to see why networks are so powerful.
也许从谷歌身上，你可以明白为什么网络是如此重要。
As Google continues to collect the billions of daily searches,
谷歌一直在收集每日数以千万计的搜索信息，
new clusters of links will rapidly emerge, forming additional and growing networks.
新的链接集群会快速产生，形成另外的新生网络。
Despite the logarithmic expansion of your network, the laws of six degrees of separation still apply.
抛开你那成对数增长的网络不谈，六度隔离理论仍旧适用。
Therefore, if you explore a close friend or acquaintances in you Facebook network,
因此，如果你观察你在脸书上的好友或者熟人，
everyone on average will be separated by six individuals or less
平均每个人会被最多六个人所隔离，
and a map of your social network will create neighborhoods linked by common connections among friends.
而你的社交网络地图，会形成由你和你的朋友们连接起来的小区。