Analyzing social media networks with NodeXL - Chapter-11 Images

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.

FIGURE 11.2 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 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.

FIGURE 11.3 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 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.

FIGURE 11.4 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 The same ego network with and without ego. The second visualization (excluding ego) shows the structure of the network more clearly.

FIGURE 11.5 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 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.

FIGURE 11.7 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 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.

FIGURE 11.8 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 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.

FIGURE 11.9 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 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.

FIGURE 11.10 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 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.

FIGURE 11.11 Copyright © 2011, Elsevier Inc. All rights Reserved Chapter 11 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.

Analyzing social media networks with NodeXL - Chapter-11 Images

by Marc Smith

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Analyzing social media networks with NodeXL - Chapter-11 Images Presentation Transcript

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