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 7
Clustering and Grouping
Analyzing Social Media Networks with NodeXL
Insights from a Connected World

2. 2Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.1
Chapter7
A network of three densely connected clusters, each shown inside a
dashed circle. Ties between clusters are rare and less dense.

3. 3Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.2
Chapter7
Unfiltered 2007 U.S. Senate co-voting network showing all 48 senators
connected to each other. Other columns in the NodeXL Edges worksheet
show the number of times each pair of senators voted the same and their
percentage agreement. A weak tie (Akaka and Allard) and a strong tie
(Akaka and Baucus) are highlighted. “Raw” visualizations like this require
refinement to display useful insights.

4. 4Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.3
Chapter7
The NodeXL Autofill Columns window with Edge Visibility Options set to
“Greater Than 0.65” and Edge Opacity Options set to a range of 0.65 (edge
opacity 10) to “The largest number in the column” (edge opacity 100).

5. 5Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.4
Chapter7
The 2007 U.S. Senate co-voting network graph after using Autofill Columns
(see Fig. 7.3), setting Vertex Shape to Label, and Edge Color to (128, 128,
192). The Fruchterman-Reingold Layout visually creates two clear groups
with a few boundary spanners in the middle after enough iterations.

6. 6Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.5
Chapter7
NodeXL Layout Options window used to increase the repulsive force
between vertices, helping spread out vertices to reduce overlap.

7. 7Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.6
Chapter7
The 2007 U.S. Senate co-voting network after applying the Find Clusters
feature and choosing to view the Graph Element – Clusters from the
NodeXL ribbon. Each of the three automatically identified clusters is given a
name, color, and shape on the Clusters worksheet.

8. 8Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.7
Chapter7
The NodeXL Cluster Vertices worksheet that maps each vertex into exactly
one cluster. For example, Collins is the only member of Cluster C14,
whereas Specter, Smith, and the others are members of Cluster C143.

9. 9Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.8
Chapter7
The Cluster Vertices worksheet used to manually map each vertex
(senators) to a cluster (political party).

10. 10Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.9
Chapter7
The NodeXL Clusters worksheet showing the four unique clusters and their
associated colors and shapes: Democrats (D) in blue, Republicans (R) in
red, and Independents (I) and Independent Democrats (ID) in dark orange.

11. 11Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.10
Chapter7
Les Misérables character co-appearance network with automatically
identified clusters represented by unique color and shape combinations.

12. 12Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 7.11
Chapter7
Lobbying Coalition network
connecting organizations
(vertices) that have jointly
filed comments on U.S.
Federal Communications
Commission policies
(edges). Vertex size
represents number of filings
and color represents
eigenvector centrality (pink
higher). Darker edges
connect organizations with
many joint filings. Vertices
were originally positioned
using Fruchterman-
Reingold and
handpositioned to respect
clusters identified by
NodeXL’s Find Clusters
algorithm.