This visualization adds the layer of "betweenness centrality" to the previous visualization. While keeping the groups formed by node types in their places, the varying size of the nodes here is based on Cytoscape's calculation of the "betweenness centrality
" from its analysis of the edges formed by the nodes, which "reflects the amount of control that this node exerts over the interactions of other nodes in the network. This measure favors nodes that join communities (dense subnetworks), rather than nodes that lie inside a community." As expected, the node representing Edward Curtis is bigger than other nodes in this visualization, and the "researchers" (e.g. Franz Boas) and the "institutions" (e.g. The Smithsonian Institution) contain more nodes with higher level of betweenness centrality than other types. This finding, however, perhaps is more attributable to either Gidley's or our own bias or emphasis on these types of social connections.
Next, we wanted to see connectivity across
the groups that we assigned by types. As one can see from the edges in the previous two visualizations, the nodes forming these groups not only interact within the group but also with the nodes in other groups. Perhaps there are also groups formed by the edges, not only by the group types that we assigned in our data. "Neighborhood Connectivity
," is a quantitative approach for assessing such connectivity, which in this case replaces the circles initially formed by node types with "neighborhoods." In this visualization, we see that the "neighborhoods" are made up of many different types of nodes.
In this example from the "neighborhood connectivity" visualization, one can see how the Harriman Expedition (1899)
brought Edward Curtis in contact with a number prominent figures of his time: John Muir, the famous naturalist; Frederick Coville, the Chief Botanist of the U.S. Department of Agriculture; and Grover Gilbert, a geologist. Other figures connected to Curtis through the Harriman Expedition, such as Edward Harriman and George Grinnell, who later organized the first Audobon Society
and served as the editor of Forest and Stream
, played important supportive roles in the development of The North American Indian,
both financially and politically.
While these visualizations do not offer a definitive identification of the entities that can be said to have the most influence within Edward Curtis' social network, they do provide a helpful graphical accompaniment to our basic understanding that The North American Indian
was not simply a benevolent, scholarly pursuit of a single photographer. It was also a business venture and an outlet for the interests of various stakeholders, reflective of the broader socio-political and academic investments in the documentation and the preservation the Native American cultural heritage, a part of the "archiving culture" of the early 20th-century. It is perhaps difficult to determine
such factors of influence or centrality in any analysis of social networks, though there are many measures to approximate
them. For example, the quantitative significance of Theodore Roosevelt, who is directly connected to Edward Curtis in our dataset through correspondence and through the contribution of the foreword to The North American Indian
, should perhaps include edges to every single node in our dataset, defined as "[Theodore Roosevelt] ["head of the state for"] [any target]." However, how would such data-ization of Theodore Roosevelt's connectivity overdetermine the role of the state and of the influence of a single prominent figure? Even as we offer this experiment with data visualization as a possible pedagogic tool and approach to contextualize Edward Curtis' work, we acknowledge and emphasize the fact of its status as a representation
of a particular set of interpretations
based on a single