Abstract
The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national well-being by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude by showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals.
Highlights
The vast streams of data that are produced by the use of automated digital services such as social media, email and mobile phones, known as ‘Big Data’, have for some time been leveraged in the private sector to assist in tasks as diverse as logistics, targeted advertising and offering personalised multimedia content
In order to understand the multiplex relationships of countries through flows of information and goods in context, we first compare all flow networks. We present their respective and collective ability to approximate crucial socioeconomic indicators and perform a network community analysis of individual networks and their multiplex communities where the most socioeconomically similar countries can be found
Big data is often related to real-time data captured through the Internet or social networks
Summary
The vast streams of data that are produced by the use of automated digital services such as social media, email and mobile phones, known as ‘Big Data’, have for some time been leveraged in the private sector to assist in tasks as diverse as logistics, targeted advertising and offering personalised multimedia content. These same data sources and methodologies have begun to be used to assist humanitarian and development organisations, allowing new ways to use data to implement, monitor and evaluate programs and policies [1]. Default.aspx); Postal Network data as used in the analysis is available as a Supporting Information file
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