I have discussed this before, but from a more abstract perspective… what is all this social network analysis stuff?

A network is a collection of things that are connected to one another.

By looking at the network, we can see the relationships between members – clusters of people, who is important, who is connected, how the relationships change over time. Some of this stuff is intuitive – like popularity or influence, but network analysis can go deeper.  For example, how many of your friends know each other? Are there network members that are bridges between groups?

We visualize the network and use symbols and colors to show patterns.

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Social media is cool because it gives us a TON of data – not only content, but conections. We can collect, analyze, visualize, and make inferences on these connections.

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Social network analysis tl;dr:

Nodes are actors.
Edges are connections.

Centrality is the number of direct connections that individuals have with others in the group.

Cohension is the ease with which a network can connect – short paths between nodes.

Density is the number of connections.

Betweenness is the shortest path between two nodes.

We can also know attributes of nodes – when did they join Twitter? How old are they? And map this onto the visualization.