Using Gephi, this data visualization explores metal trade among 80 countries in 1994. After displaying the nodes by “modularity class” two distinct groups show, and adjusting the size of the nodes by the number of connections emphasizes the recurring top ranked agents which are interestingly Finland, Poland, Slovenia, Chile, Iceland, El Salvador, Belgium, Kuwait, and Moldova.

During this lab the edges displayed in Gephi. However, when exporting the visualization all that appeared were the nodes. This is not an optimal display of the visualization but still serves to show the proximity in the image which corresponds to the strength of the observed linkages. Proximity in networks is defined by functional references: who is strongly connected to whom, or who is connected in the same way to whom. As the data represents imports by one country from another for the class of commodities designated as ‘miscellaneous manufactures of metal’, which represents high technology products or heavy manufacture, the relationship between the source and target was direct.

The data might be interesting displayed alongside a geographical representation as the comparison of geographical and network mappings can often aid in understanding how social activities affect the world by overcoming geographical distance by means of modem communication and transport technologies.

The Yufan Hu multilevel graph drawing algorithm was applied that combines a multilevel approach which effectively overcomes local minimums with another technique that approximates short and long range force efficiently.

Although the countries were surprising at first glance, some research showed that the visualization is indicative of current trends. Metal is still one of Finland’s top imports and in Moldova the major exportable items of the country include bauxite, aluminum, and steel. Raw aluminum is the top export from Iceland.

data source: http://www.casos.cs.cmu.edu/computational_tools/datasets/external/world_trade/index11.php