1.  Copyright 2011 Digital Enterprise Research Institute. All rights reserved. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Gephi Workshop 2 David Crowley Maciej Dabrowski

2. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Install netvizz app

3. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Install netvizz app

4. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Numbers will be different

5. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Open in Gephi Open Gephi – clicking should open it if not you can open it through Gephi Save a “clean” copy before playing  So you can always run through the workshop again or if you mess with it too much you can start again with the original

6. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge

7. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge So we have a hairball…. We can run a layout Force Atlas 2 Gephi designed layout – good for small to medium graphs 10,000 nodes + https://gephi.org/2011/forceatlas2-the-new-version-of-our-home-brew-layout/

8. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Force Atlas 2 Run the layout for a few seconds and press stop You should end up with a graph like this (not exactly the same or it could even be quite different)

9. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Gravity If your graph has loads of “islands” or “small clusters” dispersed then you can up the Gravity to bring them together – try gravity @ 2 and press run and stop a few seconds later

10. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Gravity (2) Gravity = 1 Gravity = 4

11. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Options Play with the other layout options  Hovering over an option will give you an explanation  Selecting them will show you what it means Important thing to remember is that this is not changing your graph this is just for visualisation i.e. same graphs but different ways to view it You could easily view this data in tabular view (Excel) but hard to get any insight from it

12. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Ranking (by degree) Degree – number of connections (not directed)

13. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Centrality

14. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Added colours (red = high degree)

15. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Graph/Network Statistics On the right hand side

16. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Network Measures Average Degree Avg. Weighted Degree Network Diameter Graph Density HITS Modularity PageRank Connected Components Avg. Clustering Components Eigenvector Centrality Avg. Path Length

17. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Network Measures Average Degree – handy to check how connected the graph is Average Weighted Degree – if the vertices have edge weights Network Diameter – average graph distance between all pairs of nodes – connected noides have graph distance = 1. Diameter is the longest graph distance between any two nodes in the network Graph Density – Measures how close the network is to complete. A complete graph has all possible edges and density = 1

18. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Network Measures HITS – measures “authority” and “quality” at each node Modularity – used for community detection – for a random network modularity = 0. Randomness is not “natural” PageRank – think of nodes as pages – simulates user clicks on links on pages Connected Components – weakly (undirected) or strongly connected (directed)

19. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Network Measures Avg. Clustering Components – The clustering coefficient (Watts-Strogatz), when applied to a single node, is a measure of how complete the neighborhood of a node is. When applied to an entire network, it is the average clustering coefficient over all of the nodes in the network. Used to find “small world” networks Eigenvector Centrality – A measure of node importance in a network based on a node’s connections (similar to PageRank) Avg. Path Length

20. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Ranking (by size) If you click on the reddish diamond shape (size/weight) You can change how you visualise your graph Changes the node sizes according to degree

21. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge Ranking (by size) Min -5 Max – 50

22. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge With Overlap Turned Off