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My name is Katerina Bohle Carbonell.
I'm a researcher and founder of NetNigma,
where we use behavioral science to help teams work better together.
We are now going to focus on
social network analysis as a way to understand collaboration patterns.
What we have done so far,
we looked at what is information exchange.
We have discussed why do people exchange information
and what are the consequences of interacting with others.
We've also looked at what is a team,
and then we have combined these two things to look at how does
communication influence innovation and productivity.
What you see here is that sociograms,
and before we're going to be analyzing this picture,
I need to share some technical terms with you.
The people are called nodes.
These are the squares with the letters in it.
Edges are the lines connecting the people.
Each line is a relationship.
In order to create this sociogram,
team members answer the question,
how often do you go to,
and then a team member's name for work-related information.
The lines in this graph show frequent interaction.
The arrow indicates the direction of that relationship.
To be sure that these terms are clear,
I am pointing them out here again.
The whole graph is called a sociogram.
E, which is circled out,
is a person which is called a Node.
Then we have the relationships, for example,
the line between F and H,
and it is called an edge.
The last thing we have is the arrow.
The arrow shows who is sending the interaction and who is receiving.
In this case, K goes to B for work-related information,
but B doesn't go to K for work-related information.