Table 1.
Summary of network measures used in the proposed activity.
| Measure | Definition and implications | Key references | |
|---|---|---|---|
| Node-level | Degree centrality | •Considers a given node’s number of direct connections •Nodes high in degree centrality have a large number of immediate exchanges of information | Borgatti (2005) |
| Closeness centrality | •Considers the average shortest path from a given node to all other nodes in the network •Nodes high in closeness centrality can reach all the other nodes in the network in a short number of steps and, therefore, can be efficient in accessing or sharing information | Wasserman and Faust (1994) | |
| Betweenness centrality | •Considers the extent to which a given node is positioned between other nodes on their shortest paths, or geodesics •Nodes high in betweenness centrality can serve as a bridge to transport information or control the interactions between other nodes | Freeman (1977), Wasserman and Faust (1994) | |
| Eigenvector centrality | •Considers the centralities of a given node’s neighbors (in contrast to degree centrality which exclusively relies on the number of connections) •Nodes high in eigenvector centrality are more influential than nodes which have a large number of connections to less central nodes | Bonacich (2007) | |
| Overall network-level | Diameter | •Measures the distance between the two nodes furthest apart in the network, or the largest geodesic distance across the entire network •Represents the maximum distance a piece of information needs to travel in a network | Yamaguchi (1994) |
| Mean geodesic distance | •Measures the average number of shortest steps between pairs of nodes •Reflects the overall connectivity of a network and impacts the extent to which information can be shared among nodes in few steps | Hanneman and Riddle (2005) | |
| Clique | •A cohesive subgroup of nodes that are all directly connected to all others in the group •Members in a clique have constraints in accessing non-redundant information if they do not have ties to nodes outside of the clique | Haythornthwaite (1996), Hanneman and Riddle (2005) | |
| Community structure | •Structures of densely connected subsets of nodes •Represents social groupings, impacting the flow of information within and across those boundaries | Girvan and Newman (2002) |
Figure 1:
Nodelist and plot of a 14-player network. The plot should be displayed during debriefing.
Figure 2:
Plots with centrality measures for the 14-player network. Node size is adjusted by each of the four centrality measures. Instructors can show these figures to students after analyzing the network structure.
Figure 3:
Nodelist and plot of a 28-player network. The plot should be displayed during debriefing.
Table 2.
Node centrality measures in the 14-player network.
| Node ID | Degree centrality | Closeness centrality | Betweenness centrality | Eigenvector centrality |
|---|---|---|---|---|
| 1 | 4 | 0.0278 | 12.5 | 0.6244 |
| 2 | 4 | 0.0278 | 2 | 0.7589 |
| 3 | 1 | 0.025 | 0 | 0.0472 |
| 4 | 6 | 0.0357 | 18 | 1 |
| 5 | 3 | 0.0263 | 0 | 0.6335 |
| 6 | 3 | 0.0323 | 7 | 0.5674 |
| 7 | 4 | 0.0323 | 7 | 0.7605 |
| 8 | 4 | 0.0385 | 42.5 | 0.6325 |
| 9 | 3 | 0.0357 | 44 | 0.1876 |
| 10 | 4 | 0.0294 | 30.5 | 0.0664 |
| 11 | 2 | 0.0222 | 0 | 0.0239 |
| 12 | 3 | 0.0227 | 0.5 | 0.0287 |
| 13 | 1 | 0.0208 | 0 | 0.157 |
| 14 | 2 | 0.0222 | 0 | 0.0239 |
Table 3.
Node centrality measures in the 28-player network.
| Node ID | Degree centrality | Closeness centrality | Betweenness centrality | Eigenvector centrality |
|---|---|---|---|---|
| 1 | 5 | 0.0106 | 48.0833 | 0.7109 |
| 2 | 8 | 0.011 | 85.6667 | 0.9748 |
| 3 | 1 | 0.0099 | 0 | 0.0402 |
| 4 | 6 | 0.0127 | 64.8333 | 1 |
| 5 | 3 | 0.0101 | 0 | 0.6345 |
| 6 | 4 | 0.0118 | 46.4167 | 0.5917 |
| 7 | 4 | 0.0119 | 35.3333 | 0.7543 |
| 8 | 5 | 0.0137 | 190.3333 | 0.6349 |
| 9 | 3 | 0.0133 | 191 | 0.1731 |
| 10 | 6 | 0.0123 | 185.5 | 0.0694 |
| 11 | 4 | 0.0104 | 110.5 | 0.0276 |
| 12 | 4 | 0.0101 | 6.5 | 0.0337 |
| 13 | 2 | 0.0085 | 0 | 0.2267 |
| 14 | 2 | 0.0094 | 0 | 0.024 |
| 15 | 3 | 0.0086 | 46 | 0.0082 |
| 16 | 1 | 0.0093 | 0 | 0.0161 |
| 17 | 2 | 0.0099 | 5.25 | 0.2759 |
| 18 | 2 | 0.0085 | 23 | 0.0075 |
| 19 | 3 | 0.0085 | 3.0833 | 0.2643 |
| 20 | 4 | 0.0073 | 27.5 | 0.0046 |
| 21 | 2 | 0.0093 | 5.4167 | 0.199 |
| 22 | 2 | 0.0094 | 0 | 0.024 |
| 23 | 2 | 0.0072 | 0 | 0.003 |
| 24 | 1 | 0.0061 | 0 | 0.0011 |
| 25 | 2 | 0.0108 | 14.5833 | 0.2118 |
| 26 | 1 | 0.0085 | 0 | 0.2266 |
| 27 | 2 | 0.0086 | 0 | 0.2953 |
| 28 | 2 | 0.0086 | 0 | 0.2953 |
Figure 4:
Plots with centrality measures for the 28-player network. Node size is adjusted by each of the four centrality measures. Instructors can show these figures to students after analyzing the network structure.