Network Analysis

[elleizar]

• [x] Degree distribution (Razielle)

• all degrees

• in degree and out degree to show authors making comments vs authors receiving replies

• take into account the # of interactions (weight)

• possibly better to plot it in log-log, similar to MSN example

• [x] Connectivity (Razielle)

Strongly Connected - nodes are connected in such a way that every vertex/node is reachable from other vertices/nodes of that subgraph Weakly Connected - nodes are unreachable from other nodes/vertices of a graph or subgraph

• similar to MSN example

• authors that are connected together

• [ ] PageRank

• returns the PageRank of the nodes in the graph.

• PageRank computes a ranking of the nodes in the graph G based on the structure of the incoming links. It was originally designed as an algorithm to rank web pages.

• [x] Clustering Coefficient (TODO)

• shows how authors are able to get more information from the neighbouring authors

• information can spread between neighbours rather than straight from the source node

• [x] Shortest Path

• [ ] Degree Centrality

• Other types of node centrality we could look at include Betweenness centrality and Closeness centrality

• [x] Print analysis into a file (TODO)

[elleizar]

@erinabila checkboxes with (TODO)

• [x] Print other number stats of the network. Include the numbers for

• nodes

• edges

• diameter
• global clustering coefficient
• average shortest path in the stats
• [x] Revisit local clustering coefficient (need help) wrote this in the Deliverable 2 doc on what I think it shows so far:

[elleizar]

Not done:

• PageRank
• Degree Centrality

PR-8 created for other analyses found here