So we’re analyzing social networks using Gephi in the #dalmooc learning analytics course:

If I have this right,

Actors (aka nodes) are the people (.e.g. email addresses)

Relations (aka edges) are the links among people (they can have signed (e.g. positive or negative) relations: For instance advice (+) vs. annoyance (-) types.

Relations can have weights.

Relations can be directed or undirected.

There are various measures that describe a group structure:

Diameter: the longest distance between any pair of two nodes in the network.

Density: The proportion of relations that are active

Decreased centrality: The number of connections for each actor

In-degree centrality: How many other nodes are trying to establish communication or are talking to a particular node.

Outgoing connections may mean how many e-mails an individual sent to somebody else

Betweenness centrality: The ease of connection with anybody else in the network

Closeness centrality: The ease or the shortest distance of a node to anybody else in the network.

Communities (modules) can form. They are subgroups

The “giant component” is the largest subgroup

I did an analysis on one of the sample datasets from a prior course (CCK11 Blogs, 6 weeks) and it produces (YES!) lovely pictures, BUT

  •     The pictures are completely different given different “layouts”
  •     It’s not very clear what it means without some identifying information – who is who?

 


If you want to try some other datasets, there are a bunch listed here:

http://snap.stanford.edu/data/index.html#citnets

NB: Some of them are too big for Gephi.

Gephi