Agent : The nodeset that represents the characters in the stories be they good guys or bad guys. That designation is handled by giving each some special attributes

Betweenness Centrality : Represents the number of people connected indirectly through another character's direct links. Quantifies the number of times a node acts as a bridge along the shortest path between two other nodes.

Boundary Spanners : People that connect disparate groups. They are often a source of innovation since they serve as a connector to the other people a cluster typically does not interact with.

Centrality : Measures one’s impact, based on how well they “connect” to other members of the network. It’s not just about having the most connections, but also where those connections lead to. It's also important how they are connected.

Characteristic Path Length : Are the friends of my friends, also my friends.

Closeness Centrality : Measures the extent to which a character is near all other characters in a network (directly or indirectly). It shows how one character might access information through their connections in the network [think grapevine]. It's how fast it will take to spread information from one character to all other characters sequentially.

Degree Centrality : The number of links to other people in the network. The immediate risk of a node for catching whatever is flowing through the network (such as a virus, or some information).

Event : New Years' Eve party or a traffic accident.

Groups : [Newman]This algorithm defines groups such that members of a group have more interconnections than do members of different groups. (There are more within-group ties than between-group ties.)

Isolates: Nodes which are not connected to any other nodes.

Knowledge : Something known to a person. Can either be a one-off piece of information or a skill set like quantum physics.

Link : If someone meets another person in a story they have a link to that person. They can also have links to places, resources, or any other nodes.

Location : The where did something happen nodeset. For the initial friends network, this will not be used but will come in for later analysis

Network : It all leads up to this. All your nodes with all their links on the screen at the same time.

Node : Represents something whether it be a person, place or thing. Sounds like the description of a noun. But it can also be something you know or have to do. It comes down to being whatever you need to show on the screen.

Nodeset : This is a group of those nodes. But they are a specific group. Like all the people or all the knowledge, or all the places represented.

Outlier : An observation that is numerically distant from the rest of the data.

PendantsNodes with only one connection to the network. These can also be outliers.

Resource : Usually a physical object that can be passed from person to person, but there are exceptions.

Small-World Network : This has both local connectivity (Large Clustering Coefficient) and global reach (small Characteristic Path Length).

A Social Network : A network is comprised of people (or organizations) connected by any sort of interaction be it family, friends, interests, or beliefs. These relationships, or networks, are displayed in a diagram where nodes [the characters] are connected by links [The connections between characters].