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:
NB: Some of them are too big for Gephi.