Network science defines three main types of influence: credibility/authority (having many inbound connections), reach (having many outbound connections), and connection/bridging (connecting different subgroups). These different types of influence emerge from analyzing the pattern of relationships in networks.

1. 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.

2. The Influence Engine:
How does network science
define and measure
'influence'?
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.

3. The Influence Engine:
How does network science
define and measure
'influence'?
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.

4. The Influence Engine:
How does network science
define and measure
'influence'?
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.

5. The Influence Engine:
How does network science
define and measure
'influence'?
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

6. The Influence Engine:
How does network science
define and measure
'influence'?
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.

7. The Influence Engine:
How does network science
define and measure
'influence'?
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

8. The Influence Engine:
How does network science
define and measure
'influence'?
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’.

9. The Influence Engine:
How does network science
define and measure
'influence'?
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 connection or bridging
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.

10. The Influence Engine:
How does network science
define and measure
'influence'?
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.

11. The Influence Engine:
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.

12. The Influence Engine:
Several ‘flavours’ of
influence
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?

13. The Influence Engine:
Several ‘flavours’ of
influence
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

14. The Influence Engine:
Several ‘flavours’ of
influence
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

15. The Influence Engine:
Several ‘flavours’ of
influence
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 .

16. The Influence Engine:
Several ‘flavours’ of
influence
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