Mapping Globalization: Visualizing the Network of Global Trade


Share / Export Citation / Email / Print / Text size:

Journal of Social Structure

International Network for Social Network Analysis

Subject: Social Sciences


eISSN: 1529-1227





Volume / Issue / page

Volume 22 (2021)
Volume 21 (2020)
Volume 20 (2019)
Volume 19 (2018)
Volume 18 (2017)
Volume 17 (2016)
Volume 16 (2015)
Volume 15 (2014)
Volume 14 (2013)
Volume 13 (2012)
Volume 12 (2011)
Volume 11 (2010)
Volume 10 (2009)
Related articles

VOLUME 11 , ISSUE 1 (December 2010) > List of articles

Mapping Globalization: Visualizing the Network of Global Trade

Manish Nag *

Citation Information : Journal of Social Structure. Volume 11, Issue 1, Pages 1-3, DOI:

License : (CC-BY-NC-4.0)

Published Online: 10-January-2020



Graphical ABSTRACT

Mapping Globalization: Visualizing the Network of Global Trade



How global is globalization? The last 20 years have witnessed an explosion of international connections and transactions: we travel more to each other’s cities, buy more of each others’ products, and are more likely to read each others’ newspapers and best-sellers. But there are severe limits on the reach and degree of globalization. European and North American newspapers are more likely to be read by an international audience than their Indian or Brazilian counterparts. Style and sophistication are still more associated with Paris than Shanghai, not to speak of Mumbai. When we speak the global language of business, science, and the arts, it sounds remarkably like English.

Even in the most globalized of arenas, the pattern of relations and connections can still look remarkably like the 19th century. Despite the prophesied rise of a “Pacific Century”, most of the global action remains rooted in the North Atlantic. While the past decades have witnessed the rise of East Asia, the Global South plays a small role in global trade. This is particularly true of commerce in manufactures and other high value-added products whose production remains concentrated in relatively wealthy countries. (The design and sales of these products, where the greatest profit can be derived, is even more concentrated). When the economies at the global margin do participate, they often do so through the sale of a single commodity or through the export of labor.

Our animation documents this by tracking global trade in 2001. Counting all possible dyadic transactions we have taken graphic photographs of four levels of trade. The first image of all global trade includes the numerous, but often insignificant, links connecting the globe. In the next image of the top 75% of trade, the number of countries involved and lines linking these are noticeably reduced (and the overall geographical concentration and centrality of the United States and Western Europe becomes clear). The next picture subtracts even further to the few commercial relationships needed to account for 50% of the total. In the last image we can see the relatively few country pairs with the largest commercial transactions adding up to 25% of the global total.


Our visualization was created using Sonoma, a new software tool that exists to create geospatial visualizations of social networks. The tool allows researchers to build maps, and then to automatically overlay social network graphs. As a result of using this tool, creating the visualizations was simply a matter of using Sonoma’s user interface to define a map projection and map colors, to upload trade network data in a matrix file, and to upload a separate file for latitude and longitude data for each actor on the map.

For our example, since nations were our actors, we positioned each graph vertex on the nation’s capital city. The latitude and longitude data was obtained from the CIA World Factbook. Once, the data files were uploaded, the Sonoma user interface was used to define visual attributes of the network graph’s vertices and ties, along with schemes for scaling the colors and widths of ties based on tie weights.

The matrix data was furnished by the Mapping Globalization website at Princeton. Though the original data provided directed matrix data for world trade, we converted this data to an undirected format by simply taking the sum of trade in both directions between each dyad of nations. The choice was made to use undirected network data because introducing directional arrows in a global map would create too much visual clutter.

Once images were created in Sonoma, an animation was rendered using Adobe Photoshop. Due to the existence of Sonoma, the real challenges in creating the visualization were more in the conception and visual design of the visualization.

Though we created visualizations for other percentages of world trade, we found that choosing the top 25, 50, 75, 100 percentages of world trade summarized the larger point of how much the network of nations shrank as we visualized smaller slices of world trade.


This is a creative animation; when all of the global trade is included it does appear as if global trade is truly global, as the map is literally filled with connections. But the story is quite different, when one only considers the top 75%, 50% or 25% of the global trade: here the marginal countries drop out of the network and only the major industrialized nations remain. This large scale visualization tells a clear story in a creative manner, but the figure could perhaps be improved by adding a bit of color to liven the picture or layer more information (such as content of trade, say). It might also be useful to make the edges more transparent, so that the map shows through even when full.


This visualization uses an interactive layout to show how regions of the world are integrated through trade. At the most integrated level when 100% of global trade is depicted, the entire world appears integrated. When that level is dropped to 75% of global trade, the picture is very different. The wealthiest nations, and within them – regions, remain. This visualization is very effective already, but perhaps a heat color pattern on the underlying picture or variable line thickness would be a nice addition, to help contextualize each ‘slice.’ The dynamic elements are rhetorically effective – the inequality jumps out in the contrast between the slices – but I wonder how effective it would be to shade ties by proportion of world trade and then layer the information as a single figure?


This map does making a striking clear visual case for the inequality among national actors involved in the global economy. Its use of edge thresholds leads us naturally to the author’s conclusion without needing to convince us with captions and supplementary material. I would love to see the edges draw with edge opacity proportional to the trade volume represented by the tie (this might yield a single image that displays all ties, but still permits those few, elite, high-volume ties to stand out).

XML Share