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来自 Princeton University 的课程

Networks Illustrated: Principles without Calculus

39 个评分

Princeton University

Networks Illustrated: Principles without Calculus

39 个评分

What makes WiFi faster at home than at a coffee shop? How does Google order its search results from the trillions of webpages on the Internet? Why does Verizon charge $15 for every GB of data we use? Is it really true that we are connected in six social steps or less? These are just a few of the many intriguing questions we can ask about the social and technical networks that form integral parts of our daily lives. This course is about exploring the answers, using a language that anyone can understand. We will focus on fundamental principles like “sharing is hard”, “crowds are wise”, and “network of networks” that have guided the design and sustainability of today’s networks, and summarize the theories behind everything from the social connections we make on platforms like Facebook to the technology upon which these websites run. Unlike other networking courses, the mathematics included here are no more complicated than adding and multiplying numbers. While mathematical details are necessary to fully specify the algorithms and systems we investigate, they are not required to understand the main ideas. We use illustrations, analogies, and anecdotes about networks as pedagogical tools in lieu of detailed equations. Please note that per Princeton University policy, no certificates, credentials or reports are awarded in connection with this course.

从本节课中

Viral Videos on YouTube

What does it take for a video to become "viral" on YouTube? In this lesson, we will take a look at some of the key factors and models that have been used to explain this phenomenon. At the core is the notion of information cascade in a network, which is the counterpart to the wisdom of crowds.

YouTube timeline4:50

Viral style and video recommendation7:36

Defining "viral"3:18

Information cascade & sequential decision making8:24

Number-Guessing Thought-Experiment3:11

First, second, and third "guessers"7:36

Analyzing cascades: Part I13:21

Analyzing Cascades: Part II10:25

Emperor's New Clothes4:34

Considerations5:14

与讲师见面

Christopher Brinton
Lecturer
Electrical Engineering
Mung Chiang
Professor
Electrical Engineering

Now, what makes an item popular to begin with?

We can break this down into two distinct factors.

The first one is intrinsic value.

You may enjoy certain music, or buy a particular product simply, because you

like or need it, regardless whether the rest of the world agrees or not.

So we say that what your doing is going to be independent of what others think.

The second class, is network effect, so, we can have intrinsic value, affecting the

popularity of a product, and also network

effect, which affects popularity of a product.

So the network effect, is that in many instances,

your decision's is going to depend upon what others do.

For one of two reasons.

First, the fact that others like your product, is naturally going to

give you some information about it's quality, appeal, and other factors.

This leads to what's known as the fallacy of the crowds, which is the exact opposite

of what we just discussed, and the wisdom

of clouds in the context of Amazon and Netflix.

And here the wisdom of crowds is going to

break down, because we no longer have that independent assumption.

[SOUND] Because, people are influenced by the crowd.

So, what this means is that, if, if you remember

this image from the videos in Amazon we, we said

that the opinions of a large number of people, is

going to be greater than the opinion of any single person.

But, what happens is when all these opinions are made public.

So when, this person's opinions is going to influence everyone else's, and

this person's opinion's also is going to influence everyone else's, and so forth.

They, are going to end up coming up

with something that's dependent upon each others' opinions.

And, in the worst case, they're all going to formulate the exact same opinion.

And therefore this is going to be in the extreme

case, no greater than any one of their opinions might be.

The specific type of fallacy crowds were going to study

here is, information cascade where we going to see that

people are going to ignore their own private information,

in favor of what the public actions are doing.

The second part of network effect that's

going to influence the popularity of a product.

Make a product more popular, is that, the value of a service

or product may depend upon the number of people that are using it.

A good example of this, is a fax machine.

Because it becomes more useful as more and more people are able to accept faxes, so

the more people that have fax machines, the more likely you would be to buy one.

The same thing with Wikipedia.

Because Wikipedia, is the whole idea of

crowd-source generation of content and crowd-source editing.

So, Wikipedia is going to become richer

with knowledge, as more entries are written.

So, you're more likely to use Wikipedia, the

more people that are on it and editing it.

And this is an example of the positive network effect, right?

So where something actually becomes better because more people are using it.

And in the other case, the network effect,

where others' people, others' opinions are giving you information.

Leading to an information cascade.

An information cascade, we can see.

Could either be a good or a bad thing, right?

So, everybody could be following the truth or

everybody could be following something that's not necessarily true.

But in any case, the key point is that

intrinsic value could lead to higher popularity of a product.

Network effects could lead to higher popularity of a product in two ways.

The first one is that other people may

follow the crowd, in terms of the information cascade.

So if they if they see more and more

people doing something, they're more likely to do it themselves.

And the second way is through the positive network effect.

Just saying that the amount of people using something, is going to

direct the influence of how likely someone is, to purchase it.

Because it's going to have a higher value.

So, our focus on the rest of this lecture,

is going to be on the fallacy of the crowds.

Specifically we're going to study an example of

information cascade, to see why it may occur.

But keep in mind that we do not have a definite answer,

as to which model, if any, is going to fit reality sufficiently well.

So, again, in this lecture, we're going to see a

large gap between the theory of things like fallacy

of the crowds and information cascade, and the practice

of things like what makes a YouTube video go viral.

[BLANK_AUDIO]

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