I chose to look at Brian Sarnacki’s project “Corruption and Reform”. There were many different interesting projects and visualizations. I focused on the Social Welfare Organizations network, which eponymously maps relationships between social welfare groups in Grand Rapids, 1914.
The visualization was easy to parse, but proved challenging to comprehend as the nodes are organizations or members of the organization. However, it was not clear what the connections between nodes meant. I then found that the connections meant that a certain person was affiliated with that organization, whether a member or volunteer.
Interactive Capabilities
The interactive network allowed the user to click on an individual or organization and check their eigenvector centrality. The eigenvector centrality is measured based on the number of connections to high-scoring nodes, i.e. a node gets a higher score if it is connected to a node with a high number of connections itself.
The network also opens up a profile page with the centrality as well as a comprehensive, clickable list of the connections and some other obscure terms. These features and capabilities helped me understand the network more effectively, but the key for nodes and connections could have been highlighted better.
