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Edges: connections between the nodes (sometimes called arcs)
Concept of networks gives us a framework for wider context, connections of history etc.
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Network Diameter: what is the longest connected/edged path through this network? Avg path: how long on average does it take to get from one random node to another any other random node? (think 6 degrees of Kevin Bacon)
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Local clustering: how many of my friends are friends (connected) with each other. This goes hand in hand with modularity, think about "communities" or "groups of friends"
Degree Distribution: what does the network look like as a whole based on their connections with one another.
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Information Flow can vary: consider bibliometrics vs. history. Bibliometrics information is flowing from cited paper to the citing paper, hence the edge would be directed that way. A historian may be more interested in the opposite.
Hive plot is a network graph that is more spatially oriented
Every network is representable by a matrix.
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