Figures and images from the book: _Analyzing social media networks with NodeXL: Insights from a connected world_

1. 1Copyright © 2011, Elsevier Inc. All rights Reserved
Chapter 11
Visualizing and Interpreting
Facebook Networks
Analyzing Social Media Networks with NodeXL
Insights from a Connected World

2. 2
Bernie Hogan is a Research Fellow at the Oxford
Internet Institute at the University of Oxford. Bernie's
work focuses on the process of networking, or
maintaining connections with other people.
His dissertation focused on the use of multiple media
for networking while his current research on Facebook
looks at the complexities of networking with multiple
groups on a single site.

3. 3Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.1
Chapter11
Example Facebook page showing a
user’s news feed.

4. 4Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.2
Chapter11
Examples of a 1.0, 1.5, and 2.0 network. In an unweighted undirected
network, the 1.0 network is simply the list of a person’s friends. The 1.5
network includes the connections between these people, and the 2.0
network includes their other friends. Facebook will enable a person to see
both the 1.0 and the 1.5 list but not the 2.0 list.

5. 5Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.3
Chapter11
A diagram showing how to construct a network from a list of friends using
the REST API friends.areFriends() query. The algorithm is written in text.

6. 6Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.4
Chapter11
The same ego network with and without ego. The second visualization
(excluding ego) shows the structure of the network more clearly.

7. 7Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.5
Chapter11
Comparing two network layouts of same graph. The first uses the default
Fruchterman-Reingold settings and the second uses 100 iterations and a
repulsion of 3.3. Clusters and bridges between these clusters are more
clearly shown in the second layout.

8. 8Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.6
Chapter11
Detail of the NodeXL Schemes button and the Scheme dialog (which
includes a categorized graph scheme).

9. 9Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.7
Chapter11
A n example category sheet to be used as a look-up table. The top row has
column label details because it has been transformed using the “Format as
Table” command.

10. 10Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.8
Chapter11
Author’s Facebook network with vertices colored by gender using a
Category table. Blue squares are male and red circles are female. Gray
hollow diamonds show individuals with no gender data. Edges connected to
vertices with missing data are silver and black otherwise. This shows that
most of the network is not clustered by gender, although there do appear to
be pockets of individuals of like type, notably a red cluster near the center
and a blue component of four people near the bottom.

11. 11Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.9
Chapter11
Complete visualization of Facebook network. Node shape corresponds to
gender (circles are female, squares are male, diamonds are unknown
through Facebook). Size is scaled betweenness (showing connectors).
Opacity is eigenvector centrality (making dense clusters visible). Color is
mapped to automatically detected clusters. Thumb-nailed images show
fellow authors in this book.

12. 12Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.10
Chapter11
NodeXL radial layout of a Facebook network. The colors represent different
clusters. All of the vertices within each cluster are ordered by degree. This
diagram shows how well the different clusters link together. It can also be
seen as sort of a pie chart for the clusters.

13. 13Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 11.11
Chapter11
NodeXL Pinwheel layout. This layout is an extension of the Friend Wheel
layout (or clustered Radial layout). The radius is scaled to betweenness
and the other attributes (size, color, and ordering are mapped to degree).
This layout gives extra information in the cluster relative to the radial layout.
One can more clearly see if high-degree nodes link to the rest of the cluster
or to other clusters. One can see if low-degree nodes link outside the
cluster as well. And clusters are still distinct despite the fact that they all
use the same color gradient. The ring around the network and the labels
were added in Illustrator.