4 how does network science define and measure 'influence'.pptx

The Influence Engine:

How does network science define and measure 'influence'?

How does network science define and measure the slippery concept known as 'influence'.

This is where the real magic of network analysis happens.

The emergence of influence as a mathematically derived consequence of a person's relationship with their neighbours is so simple and elegant, yet powerful and flexible, that one can't help feeling slightly humbled by it.



Let's begin with this interesting node here on the left of our picture.

It clearly plays an important role in binding its subgroup together and this is due to two factors.

Firstly, it has more connections than the other nodes around it.



But if we look over to the right of the picture we can see another node with the same number of connections.

But the key difference between the two nodes is the directionality of their connections.



It is the direction in which the arrows are pointing that is the second factor that makes the node on the left special.

It's difficult not to ask the question, "why are so many people pointing at this node; what is it that makes this node so interesting?"

If this was a group of music enthusiasts the answer might be that the guy in the middle is a real aficionado who knows more about music and is generally admired for his skill in identifying great new artists.

This type or flavour of influence is usually called credibility or authority. Messages or ideas, conveyed by people like this tend to be received with greater reverence or consideration.



The point being made here is that the connections established within a network's topology rarely lie.

The direction in which a connection is established it is very often a sincere reflection of the significance or respect that one individual has for another.

And as the number of those connections increases the statistical validity of the 'sample' grows and takes on a life of its own.

credibility



But what about the node over here on the right?

It's clear that this individual has been very busy reaching out to lots of other people in his or her neighbourhood.

They may indeed have something interesting or even important to say but this pattern of connections suggests it is more likely that they are shouting at people rather than being intensively listened to.

When I see people in the context of the Internet with many more outbound connections than inbound links it could be an indication that this individual is an inveterate spammer.



However, not every node with this pattern of connections is a spammer.

Very often they can be the outgoing types who reach out to people and draw them into a relationship that others may have been too shy to initiate – I guess we’ve all met people like this at parties

This illustrates another type or flavour of influence.

People who establish a lot of connections have a greater network ‘reach’ through which new ideas or messages can potentially travel to a wider audience.

reach



The third type or flavour of influence that we can see in this picture is illustrated by this node in the middle.

We know that if this guy is removed from the picture our network breaks down into two isolated subgroups that are effectively unable to communicate with one another.

Put another way, all traffic originating on one side of the network has to pass through this guy in order to reach the other side of the network, which effectively means that this person is a ‘bridge’ or ‘connector’.



Connectors can be within any network. On the one hand they play a crucial role in linking disparate subgroups together and provided the glue that gives bigger networks their cohesion.

But on the other hand they represent a key vulnerability for any network - if they are removed or ignored bad things will happen.

In communication terms these people can act as bridges across which messages can be sympathetically transmitted from one group to another.

They might not be the creators of new thoughts or opinions, but without them it can be hard for a message or an idea to break out of the social circle in which it originated and gain a bigger following in the wider marketplace.

connection or bridging



In summary we can see three types of influence emerging from the pattern of relationships in this network.

Firstly, we have credibility or authority.

Secondly, we have ‘bandwidth’ or reach.

And thirdly we have connection or bridging.


Several ‘flavours’ of influence

General Network Influence

People with the highest general influence tend to be the biggest, most credible players in a network.

They create content that generates more in-bound links than anyone else, but crucially also tend to attract links from other credible players in the network.



Network popularity

People can get a high Network Popularity score if a lot of people pick up on their content and want to link with it.

However, the key question that Network Popularity asks each node is this - how credible are your connections?



Network popularity

If lots of people link to an author's content, that’s credible.

But if most of these people have relatively low network status, as in this diagram, it can lower the popularity of a node.

lower network popularity



Network popularity

However, if the people that link into an author's content happen to be very credible, as in this picture, then that makes the content and its author even more popular too.

Put another way, you can become more popular if your friends are cool.

higher network popularity



Cool Hunters

Cool Hunters might not attract the most in-bound links to their material, and often have more outbound than inbound connections.

But rather than being indiscriminate spammers, they often have an uncanny eye for quality .



Cool Hunters

They tend to be better than most at identifying and forging links with the most credible and influential players in the network.

Keep an eye on these guys - they can show you what's hot or not, or who can start the bush fires in any brand's online ecology.

cool hunter

4 how does network science define and measure 'influence'.pptx

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