1. 1Copyright © 2011, Elsevier Inc. All rights Reserved
Chapter 9
Thread Networks
Mapping Message Boards and
Email Lists
Analyzing Social Media Networks with NodeXL
Insights from a Connected World

2. 2Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.1
Chapter9
Threaded conversation diagram showing five threads that are part of two
different topics. Each post includes a subject (e.g., Thread A), a single
author (e.g., Adam), and a time stamp (e.g., 12/10/2010 2:30 pm).
Indenting indicates placement in the reply structure. Green posts initiate
new threads (i.e., they are top-level threads), yellow posts reply directly to
green posts, orange posts reply to yellow posts, and the pink post replies to
the orange post.

3. 3Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.2
Chapter9
A n example discussion Reply network graph displayed in NodeXL, based
on the data found in Figure 9.1. The network is constructed by creating an
edge pointing from each replier to the person he or she replied to and then
merging duplicate edges. Notice that Beth has replied directly to Dave
twice, so the edge connecting them is thicker. Fiona replied to her own
message, so there is a self-loop. Greg started a thread but was not replied
to. He would normally not show up on the graph because he is not in the
edge list; however, he was manually added to the Vertices tab and his
visibility was set to “Show,” so he would appear.

4. 4Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.3
Chapter9
A Top-Level Reply network graph displayed in NodeXL based on the data
found in Figure 9.1 . The network is constructed by creating an edge
pointing from each replier to the person who started the thread (i.e., posted
the top-level message) and then merging duplicate edges. Notice how
Cathy plays a more prominent role (i.e., has a higher in-degree) than in the
standard Reply network graph (Fig. 9.2) because she started the longest
thread and all subsequent repliers link to her. Self-loops are more frequent
in this type of network because people like Cathy may respond to those
who replied to her initially, leading to a self-loop.

5. 5Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.4
Chapter9
NodeXL’s Import from Email Network dialog showing two methods to
restrict the network to messages sent to the email list. One method is to
include messages with “[css-d]” in the Subject line. The other method is to
include messages sent to the list address (css-d@lists.css-discuss.org).
Messages are also filtered to only include 2 months of data: January and
February of 2007.

6. 6Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.5
Chapter9
NodeXL Subgraph images (1.5 degree; vertex and incident edges
highlighted red) for six CSS-D contributors that fill three different social
roles within the CSS-D community. Answer people predominantly reply to
questions from isolates (i.e., those who are not connected to others).
Question people typically have a low degree themselves, but they receive
messages from those with high degree (i.e., answer people). Discussion
starters initiate long threads and receive many replies, often from people
who know each other.

7. 7Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.6
Chapter9
NodeXL map of the CSS-D email list network
for January through February of 2007 after
removing the vertex for the email list address
itself. Answer people (greener) and
discussion starters (redder) are identified by
the calculated answer person score (see
Advanced Topic: Social Role Measures).
Blue vertices have a total degree of fewer
than 15. Subgraph images (1.5) of the top
four discussion starters are shown. Vertex
size is mapped to eigenvector centrality.
Edge weight is mapped to both edge size
(1.5 – 4) and opacity (20 – 80), applying the
logarithmic scale and ignoring outliers. Like
many help-based communities, CSS-D
consists of mostly question askers with a
handful of answer people and discussion
starters.

8. 8Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.7
Chapter9
NodeXL map of the filtered version of the CSS-D email list seen in Figure 9.6 showing
only the most central members. The maximum size of vertices and edges has been
increased to more clearly draw comparisons.

9. 9Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.8
Chapter9
NodeXL map of ABC-D’s email list reply network. The current administrator (Admin)
and other members that are most central to the network are labeled. Larger vertices
have a higher eigenvector centrality and darker purple vertices have a higher
betweenness centrality. Subgraphs are shown in the worksheet to indicate each
member’s local 2-degree network neighborhood.

10. 10Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.9
Chapter9
NodeXL map of ABC-D’s email list reply network with the current administrator
removed from the network. Graph metrics are recalculated without the administrator.
Size and color mean the same thing as the prior graph (Fig. 9.5), and vertex locations
have been fixed to facilitate comparison.

11. 11Copyright © 2011, Elsevier Inc. All rights Reserved
FIGURE 9.10
Chapter9
Bimodal network connecting three Ravelry groups (i.e., forums) represented as blue
text boxes to contributors represented as circles. Edge width is based on number of
posts (with logarithmic mapping). Vertex size is based on number of completed
Ravelry projects. Maroon vertices have a blog and solid circles are either community
moderators or volunteer editors. The network helps identify important boundary
spanners (e.g., those connected to multiple groups) as well as compare groups.