# Meerkat's Law

> 네트워크 효과를 더 잘 이해하기 위한 설명. Metcalfe's Law에 대한 대안으로 The Cold Start Problem: How to Start and Scale Network Effect 2장에서 Andrew Chen이 제안.

<네트워크 효과>를 더 잘 이해하기 위한 설명. [Metcalfe's Law](https://wiki.g15e.com/pages/Metcalfe's%20Law.txt)에 대한 대안으로 [The Cold Start Problem: How to Start and Scale Network Effect](https://wiki.g15e.com/pages/The%20Cold%20Start%20Problem%20-%20How%20to%20Start%20and%20Scale%20Network%20Effect.txt) 2장에서 <Andrew Chen>이 제안.

The Allee effect → <Network effect>:

> There are many types of <social animals> that benefit by living together—whether that's from coordinating hunting to finding mates to resisting predators. More nodes in these networks are better. However, if for whatever reason the population of these social animals declines, the benefits can quickly go away, making them more susceptible to collapse. But if the population grows too quickly, and there are too many animals living in too small a space, then overpopulation negates their advantages—which causes the population to plateau. Starting to sound familiar? Yes, it's true: social animals have <network effects>, too.

[Allee threshold](https://wiki.g15e.com/pages/Allee%20threshold.txt) → <Tipping point>:

> These dynamics were first described in the [1930s](https://wiki.g15e.com/pages/1930s.txt) by <Warder Clyde Allee>, a professor at the <University of Chicago> and a pioneer of American <ecology>. His paper <Studies in animal aggregations: Mass protection against colloidal silver among goldfishes> observed that goldfish grow more rapidly and can resist water toxicity when they are in groups. … This became an important concept in <biology> because it was the first to capture the notion that there was a tippiing point - called an "Allee threshold" - where the animals would be safer and thus ultimately grow faster a a population. In other words, Allee's population curves describe a sort of ecological version of the <network effect>. …
>
> If a messeging app doesn't have enough people in it, some users will delete it. And as the user base shrinks, it becomes more likely that each user will leave, ultimately causing inactivity and collapse of the network.

<Carrying capacity> -→ Market saturation:

> But that can't last forver, because there's only so many resources … to support a finite population. … The network version of this in the technology industry happens when there is "overcrowding" from too many users. For communication apps, you might start to get too many messages. For social products, there might be too much content in feeds, …. If you don't apply spam detection, algorithmic feeds, and other ideas, quickly the networ kbecomes unusable. But add the right features to aid discovery, compat span, and increase relevance within the UI, and you can increase the carrying capacity for users.