Abstract
ABSTRACTRecent availability of geo-localized data capturing individual human activity together with the statistical data on international migration opened up unprecedented opportunities for a study on global mobility. In this paper, we consider it from the perspective of a multi-layer complex network, built using a combination of three datasets: Twitter, Flickr and official migration data. Those datasets provide different, but equally important insights on the global mobility – while the first two highlight short-term visits of people from one country to another, the last one – migration – shows the long-term mobility perspective, when people relocate for good. The main purpose of the paper is to emphasize importance of this multi-layer approach capturing both aspects of human mobility at the same time. On the one hand, we show that although the general properties of different layers of the global mobility network are similar, there are important quantitative differences among them. On the other hand, we demonstrate that consideration of mobility from a multi-layer perspective can reveal important global spatial patterns in a way more consistent with those observed in other available relevant sources of international connections, in comparison to the spatial structure inferred from each network layer taken separately.
Highlights
People travel from one country to another for different reasons and while doing so, a lot of them leave their digital traces in various kinds of digital services. This opens tremendous research opportunities through the corresponding datasets, many of which have already been utilized for different research purposes, including mobile phone records (Calabrese and Ratti 2006, Ratti et al 2006, Girardin et al 2008, Quercia et al 2010), vehicle Global Positioning System (GPS) traces (Kang et al 2013, Santi et al 2014), smart cards usage (Bagchi and White 2005, Lathia et al 2012), social media posts (Java et al 2007, Frank et al 2013, Szell et al 2014) and bank card transactions
When considering aspects of human mobility at global scale in particular, two major types of movements can be observed: an international migration (Greenwood 1985, Fagiolo and Mastrorillo 2013, Abel and Sander 2014, Tranos et al 2015) and short-term trips explored for example through geo-localized data from Twitter (Hawelka et al 2014, Sobolevsky et al 2015a) or Flickr (Paldino et al 2015, 2016, Bojic et al 2015b, 2016)
As our study aims at investigating human mobility from two different perspectives, we include three datasets where two of them capture short-term human movements such as touristic, personal or business travel, and one of them reflects long-term mobility such as people moving to another country to live there
Summary
People travel from one country to another for different reasons and while doing so, a lot of them leave their digital traces in various kinds of digital services. When considering aspects of human mobility at global scale in particular, two major types of movements can be observed: an international migration (Greenwood 1985, Fagiolo and Mastrorillo 2013, Abel and Sander 2014, Tranos et al 2015) and short-term trips explored for example through geo-localized data from Twitter (Hawelka et al 2014, Sobolevsky et al 2015a) or Flickr (Paldino et al 2015, 2016, Bojic et al 2015b, 2016). Flickr mostly reflects activity during a leisure traveling and sightseeing, while in case of Twitter, its data mostly reflect activity during spare time with internet access available which can be performed during business trips as well as leisure traveling (Kiss 2011) They are complement, as in some countries only one of these services may be popular and widely used by people. The results showed that communities detected in the three-layer network are on average much more similar to communities in the language, colony and trade networks than the ones observed in each layer separately
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